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Paper Citation Record · LEDGER

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation

As of 18 August 2026, this Paper Citation Record lists 89 of 89 outbound references and 0 inbound Pith citation observations for arXiv:2411.15763.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.15763 v1

Coverage vector

measured 89 of 89 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:58:53.834808Z

measured 89 of 89 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

89 of 89 outbound references displayed

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External citation measurements

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Outbound references

Observation 5b584ac5-93ab-4be2-b189-e7d168f5be60 · outbound

This paper cites Annotation-efficient deep learning for automatic medical image segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Annotation-efficient deep learning for automatic medical image segmentation

Reference 1

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Observation db00c723-882e-4eb5-9e2b-4e22fa116409 · outbound

This paper cites Weakly-supervised convolu- tional neural networks for vessel segmentation in cerebral angiography.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Weakly-supervised convolu- tional neural networks for vessel segmentation in cerebral angiography

Reference 2

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Observation 0e57ef8b-b5ac-4a27-bac4-37cc18d31c2c · outbound

This paper cites 3d u-net: learning dense volumetric segmentation from sparse annotation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation 3d u-net: learning dense volumetric segmentation from sparse annotation

Reference 3

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Observation 7a0d2b7f-3556-428d-9925-49f955a4b2f0 · outbound

This paper cites Auto-annotated deep segmentation for surface defect detection.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Auto-annotated deep segmentation for surface defect detection

Reference 4

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Observation 4becb7f8-f308-44e8-a35c-95451a2d4b24 · outbound

This paper cites Less Is More: A Comparison of Active Learning Strategies for 3D Medical Image Segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Less Is More: A Comparison of Active Learning Strategies for 3D Medical Image Segmentation

Reference 5

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Observation 56a5bed7-121e-4e77-b636-9a20ec263763 · outbound

This paper cites Colossal: A benchmark for cold-start active learning for 3d medical image segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Colossal: A benchmark for cold-start active learning for 3d medical image segmentation

Reference 6

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Observation 1ab9cb74-7b91-407b-83d7-3718a034c0de · outbound

This paper cites Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning

Reference 7

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Observation 8e0b0785-737c-49dc-9e65-a3c2468d9668 · outbound

This paper cites Scribble-based hierarchical weakly supervised learning for brain tumor segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Scribble-based hierarchical weakly supervised learning for brain tumor segmentation

Reference 8

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Observation 64e836e2-b6a9-4b9c-8841-e11f3e20a617 · outbound

This paper cites Scribble2d5: Weakly-supervised volumetric image segmentation via scribble annotations.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Scribble2d5: Weakly-supervised volumetric image segmentation via scribble annotations

Reference 9

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Observation c8e89811-5161-45e1-90c1-f86b79ef11ef · outbound

This paper cites Box2mask: Weakly supervised 3d semantic instance segmentation using bounding boxes.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Box2mask: Weakly supervised 3d semantic instance segmentation using bounding boxes

Reference 10

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Observation b54deaa5-7925-42dc-9759-2537e2edf7fc · outbound

This paper cites Weakly supervised segmentation with point annotations for histopathology images via contrast-based variational model.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Weakly supervised segmentation with point annotations for histopathology images via contrast-based variational model

Reference 11

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Observation 0eb8725b-63fe-42b8-9373-c29583398088 · outbound

This paper cites Affinity attention graph neural network for weakly supervised semantic segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Affinity attention graph neural network for weakly supervised semantic segmentation

Reference 12

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Observation e4542ca9-e1a5-4604-a3c4-0c3985f51c3d · outbound

This paper cites Comparative evaluation of conventional and deep learning methods for semi-automated segmentation of pulmonary nodules on ct.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Comparative evaluation of conventional and deep learning methods for semi-automated segmentation of pulmonary nodules on ct

Reference 13

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Observation 33ab2235-7dc6-43e4-bc70-e1e5a4659c55 · outbound

This paper cites Semi-automated and interactive segmentation of contrast-enhancing masses on breast dce-mri using spatial fuzzy clustering.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Semi-automated and interactive segmentation of contrast-enhancing masses on breast dce-mri using spatial fuzzy clustering

Reference 14

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Observation 40e49b5e-b573-4eea-bd60-e8c2eb2f0fdd · outbound

This paper cites Interactive segmentation of medical images through fully convolutional neural networks.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Interactive segmentation of medical images through fully convolutional neural networks

Reference 15

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Observation 8c3a4c33-04d4-4955-b0fb-2e824fd93c44 · outbound

This paper cites An unsupervised semi-automated pulmonary nodule segmentation method based on enhanced region growing.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation An unsupervised semi-automated pulmonary nodule segmentation method based on enhanced region growing

Reference 16

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Observation aac59e18-89e5-4aa6-b691-a4c7d8f0be45 · outbound

This paper cites Learning to segment from scrib- bles using multi-scale adversarial attention gates.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Learning to segment from scrib- bles using multi-scale adversarial attention gates

Reference 17

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Observation 421313b2-e521-41d5-b956-27d7ec3c19c7 · outbound

This paper cites Scribble-supervised medical image segmentation via dual-branch network and dynamically mixed pseudo labels supervision.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Scribble-supervised medical image segmentation via dual-branch network and dynamically mixed pseudo labels supervision

Reference 18

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Observation ffbb600b-b4a2-4a25-a8a5-e295ba781e7a · outbound

This paper cites Transformer based multiple instance learning for weakly supervised histopathology image segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Transformer based multiple instance learning for weakly supervised histopathology image segmentation

Reference 19

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Observation 1fa8b51c-bd2c-4193-a2d5-f7fc12fa94bd · outbound

This paper cites Multi-scale feature similarity-based weakly supervised lymphoma segmentation in pet/ct images.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Multi-scale feature similarity-based weakly supervised lymphoma segmentation in pet/ct images

Reference 20

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Observation ad240444-591c-4780-ac4e-a10ce72b9ed1 · outbound

This paper cites Max pooling with vision transformers reconciles class and shape in weakly supervised semantic segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Max pooling with vision transformers reconciles class and shape in weakly supervised semantic segmentation

Reference 21

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Observation 782965bb-7fa6-44e5-a085-aa763f3ae49b · outbound

This paper cites Boosting active learning via improving test performance.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Boosting active learning via improving test performance

Reference 22

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Observation 55402a3d-33e9-469d-a907-706f043fa061 · outbound

This paper cites Deep bayesian active learning with image data.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep bayesian active learning with image data

Reference 23

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Observation 4b34e1e3-6c52-413c-a65a-ac0a7c4dbae5 · outbound

This paper cites Deep Bayesian Active Learning, A Brief Survey on Recent Advances.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep Bayesian Active Learning, A Brief Survey on Recent Advances

Reference 24

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Observation 9391bbda-281d-4b4e-8a36-001d894b2361 · outbound

This paper cites Batchbald: Efficient and diverse batch acquisition for deep bayesian active learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Batchbald: Efficient and diverse batch acquisition for deep bayesian active learning

Reference 25

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Observation 37be0db0-9dd6-4da4-8282-59baaca0b08b · outbound

This paper cites Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study

Reference 26

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Observation 1650041b-3efc-4ad3-9c6e-6fdecdc12535 · outbound

This paper cites The power of ensembles for active learning in image classification.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation The power of ensembles for active learning in image classification

Reference 27

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Observation c47d6a11-5dc4-4498-a669-bf2b4c7cce92 · outbound

This paper cites Large-Scale Visual Active Learning with Deep Probabilistic Ensembles.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Large-Scale Visual Active Learning with Deep Probabilistic Ensembles

Reference 28

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Observation dc3d0450-cd1e-48b3-9eb7-981dd5cb5dc9 · outbound

This paper cites Deep Ensemble Bayesian Active Learning : Addressing the Mode Collapse issue in Monte Carlo dropout via Ensembles.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep Ensemble Bayesian Active Learning : Addressing the Mode Collapse issue in Monte Carlo dropout via Ensembles

Reference 29

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Observation 547420b3-3c2a-4b89-8863-3d37d07416ac · outbound

This paper cites A simple yet powerful deep active learning with snapshots ensembles.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation A simple yet powerful deep active learning with snapshots ensembles

Reference 30

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Observation 1ade6a46-d9ff-4dc3-b4d5-6fc8458f654b · outbound

This paper cites Active learning for medical image segmentation with stochastic batches.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Active learning for medical image segmentation with stochastic batches

Reference 31

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Observation 8dfd2a5f-b105-4139-8da1-eb42353a2f19 · outbound

This paper cites One-bit active query with contrastive pairs.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation One-bit active query with contrastive pairs

Reference 32

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Observation 324f529f-fc29-4269-8cab-68333993e8f3 · outbound

This paper cites Active Learning by Acquiring Contrastive Examples.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Active Learning by Acquiring Contrastive Examples

Reference 33

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Observation 5ec6ce84-e666-4cf4-a93c-a943a2572f76 · outbound

This paper cites When Contrastive Learning Meets Active Learning: A Novel Graph Active Learning Paradigm with Self-Supervision.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation When Contrastive Learning Meets Active Learning: A Novel Graph Active Learning Paradigm with Self-Supervision

Reference 34

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Observation 2699ab05-68b9-4e8b-8880-e862c0d27677 · outbound

This paper cites Deep Active Learning with Contrastive Learning Under Realistic Data Pool Assumptions.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep Active Learning with Contrastive Learning Under Realistic Data Pool Assumptions

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation df930e20-1c48-4326-8d1d-11f4f0ed349b · outbound

This paper cites Hyperbolic Active Learning for Semantic Segmentation under Domain Shift.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Hyperbolic Active Learning for Semantic Segmentation under Domain Shift

Reference 36

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Observation 12f49777-9fac-43b2-9f36-d6f988668031 · outbound

This paper cites Active Learning for Convolutional Neural Networks: A Core-Set Approach.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Active Learning for Convolutional Neural Networks: A Core-Set Approach

Reference 37

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source=pdf_text observed=2026-08-12T13:58:53.643184Z digest=sha256:183bd83222bb84653fe59193719298fe4268168b78570d6b38a453c6df02dfd8

Observation 4757a74f-25f5-4051-a24c-89e67aef096a · outbound

This paper cites Sequential graph convolutional network for active learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Sequential graph convolutional network for active learning

Reference 38

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raw_fallback, observed 2026-08-12T13:58:54.552651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.646638Z digest=sha256:7d21017ae5f48902cfaa242ef33bc037b26b65e901142b266ec96e227eb691a2

Observation f3cedfd5-2baf-48a7-be49-e39527b37207 · outbound

This paper cites Active Learning on a Budget: Opposite Strategies Suit High and Low Budgets.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Active Learning on a Budget: Opposite Strategies Suit High and Low Budgets

Reference 39

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source=pdf_text observed=2026-08-12T13:58:53.649602Z digest=sha256:6d15f6f9a54624af64d08c9882a8c38bc9ed8faddfd7795ac03fdb8e421444fd

Observation 0c7891b3-f3bb-4e2d-9784-77f40fb7052d · outbound

This paper cites Variational adversarial active learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Variational adversarial active learning

Reference 40

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raw_fallback, observed 2026-08-12T13:58:54.541789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.653350Z digest=sha256:8610aa27a69a4a604a1317777e1f79aabb24433d64bc85ce3600769d490512f0

Observation 038d4da8-0630-42cd-893d-50287c082da7 · outbound

This paper cites Task-aware variational adversarial active learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Task-aware variational adversarial active learning

Reference 41

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raw_fallback, observed 2026-08-12T13:58:54.529483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.656861Z digest=sha256:263b88acbba999e293643f7507873349c407e0a97b7f1661bd7ccb8c9a8aeace

Observation 3454eca2-b506-4823-9412-68f7ca62a25c · outbound

This paper cites Towards robust and reproducible active learning using neural networks.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Towards robust and reproducible active learning using neural networks

Reference 42

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raw_fallback, observed 2026-08-12T13:58:54.517307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.660583Z digest=sha256:3b3c85039f2f09b60b73c15f11fd050dbfb610820cc050f8d0484eee57dce433

Observation 78cc702f-e323-4f82-af24-19c43a6c039e · outbound

This paper cites Improved deep metric learning with multi-class n-pair loss objective.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Improved deep metric learning with multi-class n-pair loss objective

Reference 43

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no resolver link, observed 2026-08-12T13:58:53.664499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.664499Z digest=sha256:cba389000dcd26929c664cef9fd0e75afeda8b5e83facc9e78f02742ab5fc6ca

Observation 73a08c38-bc98-48ac-b210-3b7897ead11f · outbound

This paper cites Contrastive learning of global and local features for medical image segmentation with limited annotations.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Contrastive learning of global and local features for medical image segmentation with limited annotations

Reference 44

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verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.498136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.667988Z digest=sha256:e7d34ab5d366a9ec9a29b59c04b1de6a8769def559669ef0b74c0903fbac42ca

Observation ef74e5cf-00d8-4808-ad66-dcf92739e863 · outbound

This paper cites 3d self-supervised methods for medical imaging.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation 3d self-supervised methods for medical imaging

Reference 45

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raw_fallback, observed 2026-08-12T13:58:54.486090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.671531Z digest=sha256:35c4040e3848ac2b59e9c4d56b21a55ca295d16d6f82a982993f6cf4ca3493e0

Observation 63fdb470-8e6a-4b11-8661-d1d4a50989bd · outbound

This paper cites Are binary annotations sufficient? video moment retrieval via hier- archical uncertainty-based active learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Are binary annotations sufficient? video moment retrieval via hier- archical uncertainty-based active learning

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.474520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.676125Z digest=sha256:8dade2fca32b1e269967cd66ab925051660ca7e6673e198cf599a353fa212439

Observation 489a1d8f-10e3-49d8-9ead-ff4350a56e07 · outbound

This paper cites Active learning for domain adaptation: An energy-based approach.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Active learning for domain adaptation: An energy-based approach

Reference 47

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raw_fallback, observed 2026-08-12T13:58:54.464087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.680886Z digest=sha256:b940d131365e1026d5874db62f8921e3adf0a57decfa98f18ec3de75c5a48f3a

Observation 9d3eb0ca-b3c1-4bbc-9c17-5bf5c4f9ef3a · outbound

This paper cites Extending contrastive learning to unsupervised coreset selection.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Extending contrastive learning to unsupervised coreset selection

Reference 48

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raw_fallback, observed 2026-08-12T13:58:54.453967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.684610Z digest=sha256:a9f1c6a888ae02739902da84304d2cfaf00e1b72eb4462453b3b327e6d564b34

Observation 9f25df4d-cfab-446b-9668-8057bbea9c1d · outbound

This paper cites One-shot active learning for image segmentation via contrastive learning and diversity-based sampling.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation One-shot active learning for image segmentation via contrastive learning and diversity-based sampling

Reference 49

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raw_fallback, observed 2026-08-12T13:58:54.443022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.688223Z digest=sha256:7a4d6e35d3fa19684c87c71eecd68f7823ff5dc9a0ac106dd5cd085bf62c3198

Observation 99b2c045-7ed6-4c11-9ef4-943a4eb4ff5c · outbound

This paper cites Deep metric learning for computer vision: A brief overview.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep metric learning for computer vision: A brief overview

Reference 50

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.691906Z digest=sha256:763f1e892e26feca815edfd348c2b41c732dec20bd668c2495f3c2e2bfed719e

Observation b8ab2af1-d88e-4e85-bd59-19a38124ca8c · outbound

This paper cites Facenet: A unified embedding for face recognition and clustering.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Facenet: A unified embedding for face recognition and clustering

Reference 51

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.695635Z digest=sha256:1b0f250906d6b55fb13ee9acc3cdcdb5a1fa9d6ca4f12cc0594008a7686559a1

Observation c5c1d086-f8a6-43b9-98cd-1efac634996c · outbound

This paper cites A discriminative feature learning approach for deep face recognition.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation A discriminative feature learning approach for deep face recognition

Reference 52

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raw_fallback, observed 2026-08-12T13:58:54.409367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.699061Z digest=sha256:0b58e135e0ccc1eb292e8725369ac9a06001118bef21f06ad2784854366aa242

Observation 7bbaa1f8-447d-4715-9005-a2e9aab942d2 · outbound

This paper cites Arcface: Additive angular margin loss for deep face recognition.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Arcface: Additive angular margin loss for deep face recognition

Reference 53

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raw_fallback, observed 2026-08-12T13:58:54.398359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.702593Z digest=sha256:e4025238e81e6e37c4f11dbeff88ec173883c3dcb2330b56ca34e50b971b5e31

Observation 6aa23f85-6fb1-4bf4-8f08-84388b584203 · outbound

This paper cites Sub-center arcface: Boosting face recognition by large-scale noisy web faces.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Sub-center arcface: Boosting face recognition by large-scale noisy web faces

Reference 54

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.706098Z digest=sha256:8b821bf4f2af2252f4166ae1b9137e062429fcd34cee453179789daaabf00dec

Observation df420792-b41c-4ec0-a744-7c3935bcbd9f · outbound

This paper cites No fuss distance metric learning using proxies.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation No fuss distance metric learning using proxies

Reference 55

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raw_fallback, observed 2026-08-12T13:58:54.376458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.710093Z digest=sha256:21153b7cf9f88309f375aa01ccb3d0026ee489017265903839bd6fb18927d895

Observation c95a5596-6de7-4e57-8c47-9ec8291623ef · outbound

This paper cites Proxynca++: Revisiting and revitalizing proxy neighborhood component analysis.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Proxynca++: Revisiting and revitalizing proxy neighborhood component analysis

Reference 56

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raw_fallback, observed 2026-08-12T13:58:54.365401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.713345Z digest=sha256:6e7e4ff8c5d98b064dab211f1019b556fa97f07367220a5985d45c66c32e4c1f

Observation 29940290-0f72-4a11-9377-ddd8fac68f83 · outbound

This paper cites Napreg: nouns as proxies regularization for semantically aware cross-modal embeddings.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Napreg: nouns as proxies regularization for semantically aware cross-modal embeddings

Reference 57

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raw_fallback, observed 2026-08-12T13:58:54.353843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.716860Z digest=sha256:1333c8a9eb8d872779916782ccad10ae36ca811a0b3db7973662388c3ca97ac5

Observation 688d206e-a501-4725-bf71-0c9e813ba345 · outbound

This paper cites Integrating language guidance into vision- based deep metric learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Integrating language guidance into vision- based deep metric learning

Reference 58

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.719974Z digest=sha256:4321db29d6b6c6a960dffd8fc8315b8f9fb9b1d90650823f17b17d4822f741a7

Observation b288644d-4514-470f-9172-ad4c8705370d · outbound

This paper cites Ensemble deep manifold similarity learning using hard proxies.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Ensemble deep manifold similarity learning using hard proxies

Reference 59

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.724926Z digest=sha256:fdb62ec1e997561fcf94d5d34869bc2a2786d1d19670b840088f3a5ce6583e81

Observation 2a88b370-33f9-495c-84a1-f32c0779e8f7 · outbound

This paper cites Deep metric learning with bier: Boosting independent embeddings robustly.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep metric learning with bier: Boosting independent embeddings robustly

Reference 60

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.728403Z digest=sha256:2f7c4eafa8689ea485fae641ba0c724408d05a1f4daed690e826b031c880426a

Observation c1a1d3ff-980b-42e5-96fe-5f4078a2d9ee · outbound

This paper cites Softtriple loss: Deep metric learning without triplet sampling.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Softtriple loss: Deep metric learning without triplet sampling

Reference 61

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raw_fallback, observed 2026-08-12T13:58:54.307963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.732450Z digest=sha256:faf8b1ddb93cc02be99c484c1f2e424e6f6698f66378939c726f3472d8521302

Observation 6251cf03-c96b-4384-ae3d-aae2cee89759 · outbound

This paper cites Mic: Mining interclass characteristics for improved metric learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Mic: Mining interclass characteristics for improved metric learning

Reference 62

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raw_fallback, observed 2026-08-12T13:58:54.296481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.736563Z digest=sha256:6a43480f1563a281edac8e89c7c6f2e871a46eb62e4bcd4b44025c2628ba86fd

Observation 9c04bfa2-42ed-4845-8841-f06685c2bbed · outbound

This paper cites Deep randomized ensembles for metric learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep randomized ensembles for metric learning

Reference 63

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raw_fallback, observed 2026-08-12T13:58:54.284042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.740611Z digest=sha256:d90548a63a2310fecbf8a12ebcdeb649990696760321280d28b9798a639aabbf

Observation 5e0d3040-d483-4402-b62f-dbfcbdb6c440 · outbound

This paper cites Deep factorized metric learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep factorized metric learning

Reference 64

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raw_fallback, observed 2026-08-12T13:58:54.272118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.744490Z digest=sha256:1d8c6f2da0c6c251c0ff5102a0d0570827c419df0b042b4b24459dfa464aadfd

Observation c46cf85d-5deb-4457-aeb5-6825d06fcdc4 · outbound

This paper cites Deep semi-supervised metric learning with mixed label propagation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep semi-supervised metric learning with mixed label propagation

Reference 65

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raw_fallback, observed 2026-08-12T13:58:54.260376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.748282Z digest=sha256:e02151179dca1f3d95f2df758afdfc2ec9e18b5cbd0739d736f99a58ee7cbba6

Observation a5b42630-f910-4602-9fc7-1ef277908cb7 · outbound

This paper cites Semi-supervised metric learning: A deep resurrection.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Semi-supervised metric learning: A deep resurrection

Reference 66

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raw_fallback, observed 2026-08-12T13:58:54.249004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.751944Z digest=sha256:89451b5d49b22a658a7483f98cf15016357a08ee044002bc43cb39936496d184

Observation 28a15147-c26a-4da6-90b1-53dec733bec8 · outbound

This paper cites Self-supervised learning for medical image analysis using image context restoration.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Self-supervised learning for medical image analysis using image context restoration

Reference 67

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raw_fallback, observed 2026-08-12T13:58:54.236570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.756232Z digest=sha256:524dcb1fc707339cdf0ee915df3e86732afe4e534e8c939c732cb6bc7385c542

Observation 3fc296b6-4518-496a-9777-28985ae2a993 · outbound

This paper cites wav2vec 2.0: A framework for self-supervised learning of speech representations.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation wav2vec 2.0: A framework for self-supervised learning of speech representations

Reference 68

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no resolver link, observed 2026-08-12T13:58:53.759927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.759927Z digest=sha256:58d01708da2862f0e82ce72e37f8882fd26d1e939cd229776819fa3f71b6aa41

Observation 22cf2238-fecc-42db-9abb-c068272c4fd0 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Learning transferable visual models from natural language supervision

Reference 69

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no resolver link, observed 2026-08-12T13:58:53.763498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.763498Z digest=sha256:a1f0ae5b29656414cfb6f0b7f301cb01df526978b427c34a72b5980148bd3ca7

Observation 288d04d8-49ef-45b5-9c95-023accc1c128 · outbound

This paper cites A simple framework for contrastive learning of visual representations.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation A simple framework for contrastive learning of visual representations

Reference 70

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raw_fallback, observed 2026-08-12T13:58:54.213294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.767042Z digest=sha256:b5fc162cffe02ef6fd4df70da151aabffb910c4e73c85520545e2b23ffe2b6bd

Observation 2331e731-dce0-4751-8b81-1e065cf64687 · outbound

This paper cites Suggestive annotation: A deep active learning framework for biomedical image segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Suggestive annotation: A deep active learning framework for biomedical image segmentation

Reference 71

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no resolver link, observed 2026-08-12T13:58:53.770934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation bb7e93ad-506d-4e37-b14d-41e926b329a5 · outbound

This paper cites Diminishing uncertainty within the training pool: Active learning for medical image segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Diminishing uncertainty within the training pool: Active learning for medical image segmentation

Reference 72

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.775402Z digest=sha256:a72626fda063335d88fa466e577f2bb710496878d4b8f19db2905f0f7d62cde1

Observation 6868091f-9105-483a-95aa-d7529d4efcd7 · outbound

This paper cites Hierarchical self-supervised learning for medical image segmentation based on multi-domain data aggregation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Hierarchical self-supervised learning for medical image segmentation based on multi-domain data aggregation

Reference 73

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.779228Z digest=sha256:0ea78c16a39388f6a351627956b7eae589dccd631605505255a9d2053819bd94

Observation 4cf7c405-423c-4536-8577-8c0607f95725 · outbound

This paper cites Supervised contrastive learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Supervised contrastive learning

Reference 74

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Observation e2d8c5de-6ff3-4fbc-804d-fb756fd5e7c3 · outbound

This paper cites Deep residual learning for image recognition.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep residual learning for image recognition

Reference 75

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.786545Z digest=sha256:e565a4fe25ca99c6219b5f13bff3bc43bf43a82b86c2132b6a7f263c2cfac64e

Observation 9243e869-751d-4a07-b655-46c4986446ca · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation U-net: Convolutional networks for biomedical image segmentation

Reference 76

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source=pdf_text observed=2026-08-12T13:58:53.790132Z digest=sha256:516deebdc1eb03ed9adfcccaa821594d58f4fd168ea6ab5aff59cf151456d607

Observation 4efda970-5a76-4ef5-a067-81b813e86c90 · outbound

This paper cites Lvm-med: Learning large-scale self-supervised vision models for medical imaging via second-order graph matching.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Lvm-med: Learning large-scale self-supervised vision models for medical imaging via second-order graph matching

Reference 77

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.793388Z digest=sha256:8893f127e460229d5a78bc4a262ea7cc81a1918db4f9d9cc7d66eef623ad580e

Observation 79f93cbc-5a6f-41d4-894e-36ca918fb5ab · outbound

This paper cites Deep learning techniques for automatic mri cardiac multi-structures segmentation and diagnosis: is the problem solved? IEEE transactions on medical imaging, 37(11):2514–2525, 2018.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep learning techniques for automatic mri cardiac multi-structures segmentation and diagnosis: is the problem solved? IEEE transactions on medical imaging, 37(11):2514–2525, 2018

Reference 78

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Observation 08d74b8c-37e4-4e6e-ab02-9f070c411e33 · outbound

This paper cites Alper Selver, O˘guz Dicle, Mustafa Barı¸ s, and N.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Alper Selver, O˘guz Dicle, Mustafa Barı¸ s, and N

Reference 79

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.800559Z digest=sha256:c0ccf3a2f92c644ea989498549c4ca95c679886eee0e97d7f05d47c0d15db89b

Observation ccf38707-e61a-4f46-872c-b75aa75eb9a8 · outbound

This paper cites Bayeseg: Bayesian modeling for medical image segmentation with interpretable generalizability, 2023.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Bayeseg: Bayesian modeling for medical image segmentation with interpretable generalizability, 2023

Reference 80

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.803727Z digest=sha256:b5c82e763360db9552ec04966738319e234222816be7544a722779265f199141

Observation 0598ff89-c2d5-4c86-8551-3d824342a263 · outbound

This paper cites Multivariate mixture model for myocardial segmentation combining multi- source images.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Multivariate mixture model for myocardial segmentation combining multi- source images

Reference 81

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raw_fallback, observed 2026-08-12T13:58:54.120247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.806398Z digest=sha256:929c87db2ef060f75a0de40081bc7d456a89d62657ba608016895d577f1e5d92

Observation bd3c5c17-cc4d-4c8d-a795-51bcebfb3fc2 · outbound

This paper cites Minimizing estimated risks on unlabeled data: A new formula- tion for semi-supervised medical image segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Minimizing estimated risks on unlabeled data: A new formula- tion for semi-supervised medical image segmentation

Reference 82

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.809489Z digest=sha256:5cf94bd1af7a59c69e0345de545b2272a646969999208425e57eb9617b3f74da

Observation 41e3df8b-a875-4b64-b331-7a2aadd85d2e · outbound

This paper cites CycleMix: A Holistic Strategy for Medical Image Segmentation from Scribble Supervision.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation CycleMix: A Holistic Strategy for Medical Image Segmentation from Scribble Supervision

Reference 83

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local_arxiv, observed 2026-08-12T13:58:53.887267Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.812807Z digest=sha256:83624749350565007ee0dc6b1282159393ccf0ce65806f1b5936211f88b7e6b9

Observation 1415cff2-7bd8-47dd-b563-0246dc6bbf81 · outbound

This paper cites A benchmark dataset and evaluation methodology for video object segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation A benchmark dataset and evaluation methodology for video object segmentation

Reference 84

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source=pdf_text observed=2026-08-12T13:58:53.816677Z digest=sha256:1b90386a1877ffdb1a6ba7908fa62d2d15692c0659aaf654d0fba682e37f30a9

Observation 64f37caf-1be4-4cb2-8d25-2c343a89fb7c · outbound

This paper cites The 2017 DAVIS Challenge on Video Object Segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation The 2017 DAVIS Challenge on Video Object Segmentation

Reference 85

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source=pdf_text observed=2026-08-12T13:58:53.820229Z digest=sha256:9f2284d2eca195495dffe588c5cd1a3015aef908cd0cc99f8d120c7b3d7579ba

Observation 35774759-8cf3-49f3-bb60-863d924dc325 · outbound

This paper cites Reliable delineation of clinical target volumes for cervical cancer radiotherapy on ct/mr dual-modality images.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Reliable delineation of clinical target volumes for cervical cancer radiotherapy on ct/mr dual-modality images

Reference 86

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.824163Z digest=sha256:5f3a5a4a432e7c9e57107677caca07643247d6d02c890630fc8ca5deee699da1

Observation 5e969f19-61fe-419b-b415-bb5033861aad · outbound

This paper cites Domain and User-Centered Machine Learning for Medical Image Analysis.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Domain and User-Centered Machine Learning for Medical Image Analysis

Reference 87

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raw_fallback, observed 2026-08-12T13:58:54.079905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.827671Z digest=sha256:9048a964b05d5eb80ea3630b727e116dab8d342c0e48849bbfd5ba5c735d53b8

Observation deb35c5f-e1a1-49d6-b579-dca9b55aedfb · outbound

This paper cites Deep learning algorithm for auto-delineation of high-risk oropharyngeal clinical target volumes with built-in dice similarity coefficient parameter optimization function.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep learning algorithm for auto-delineation of high-risk oropharyngeal clinical target volumes with built-in dice similarity coefficient parameter optimization function

Reference 88

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.831162Z digest=sha256:7ad6a025d200a3c3c85baee32a368ae118a93bac7733e295a4cf09d42c13eacf

Observation e4691c2a-c8bc-4328-8028-35763be2c596 · outbound

This paper cites Automatic detection of contouring errors using convolutional neural networks.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Automatic detection of contouring errors using convolutional neural networks

Reference 89

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raw_fallback, observed 2026-08-12T13:58:54.057324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:58:53.834808Z digest=sha256:862a0cfbab1b388bfb6195687590ef4036a2477ea963b6fa3c45173abf8dbe5d

Pith citing papers

No inbound Pith citation observations are available.