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Paper Citation Record · LEDGER

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion

As of 9 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2509.09298.

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

pith.paper-citation-record.v1
2509.09298 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T19:24:39.898595Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

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49 of 49 outbound references displayed

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Outbound references

Observation 5169a441-ea95-4108-a24d-97b246508964 · outbound

This paper cites Digital processing of synthetic aperture radar data.Artech house, 1(3):108– 110, 2005.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Digital processing of synthetic aperture radar data.Artech house, 1(3):108– 110, 2005

Reference 1

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Observation 87de5b93-062c-4d55-895f-faf14fc055b8 · outbound

This paper cites Atrnet-star: A large dataset and benchmark towards remote sensing object recognition in the wild.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Atrnet-star: A large dataset and benchmark towards remote sensing object recognition in the wild

Reference 2

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Observation f4a5635d-ef71-4e21-bc8e-b6d5e2fb3c6e · outbound

This paper cites Automatic target recognition on synthetic aperture radar imagery: A survey.IEEE Aerospace and Electronic Systems Magazine, 36(3):56–81, 2021.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Automatic target recognition on synthetic aperture radar imagery: A survey.IEEE Aerospace and Electronic Systems Magazine, 36(3):56–81, 2021

Reference 3

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Observation 6c59a75f-6c18-4aac-95bd-2b6d40488a17 · outbound

This paper cites Diffdet4sar: Diffusion-based aircraft target detection network for sar images.IEEE Geoscience and Remote Sensing Letters, 21:1–5, 2024.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Diffdet4sar: Diffusion-based aircraft target detection network for sar images.IEEE Geoscience and Remote Sensing Letters, 21:1–5, 2024

Reference 4

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Observation 9b5b6bd8-2485-47d8-ac45-5a10caa998f9 · outbound

This paper cites Sardet-100k: Towards open-source benchmark and toolkit for large-scale sar object detection.Advances in Neural Information Processing Systems, 37:128430–128461, 2024.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Sardet-100k: Towards open-source benchmark and toolkit for large-scale sar object detection.Advances in Neural Information Processing Systems, 37:128430–128461, 2024

Reference 5

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Observation 9417f7d1-1f40-491a-b6cc-9301a70ef0a7 · outbound

This paper cites Saratr-x: Towards building a foundation model for sar target recognition.IEEE Transactions on Image Processing, 2025.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Saratr-x: Towards building a foundation model for sar target recognition.IEEE Transactions on Image Processing, 2025

Reference 6

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Observation 9bdb8eea-46e1-48ac-8596-2f5eafe4f7c3 · outbound

This paper cites Statistical analysis of high-resolution sar ground clutter data.IEEE Transactions on Geoscience and Remote sensing, 45(3):566–575, 2007.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Statistical analysis of high-resolution sar ground clutter data.IEEE Transactions on Geoscience and Remote sensing, 45(3):566–575, 2007

Reference 7

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Observation c66c2826-2089-4d80-91e1-8561185084b0 · outbound

This paper cites Irasnet: Improved feature-level clutter reduction for domain generalized sar-atr.IEEE Transactions on Aerospace and Electronic Systems, pages 1–18, 2025.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Irasnet: Improved feature-level clutter reduction for domain generalized sar-atr.IEEE Transactions on Aerospace and Electronic Systems, pages 1–18, 2025

Reference 8

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Observation 4bea3a4c-0efd-4658-8423-05fde5920276 · outbound

This paper cites an unresolved cited work.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Unresolved cited work

Reference 9

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Observation 7027ab94-3e05-457b-8112-7c3ff2349b3a · outbound

This paper cites Learning invariant representation via contrastive feature alignment for clutter robust sar atr.IEEE Geoscience and Remote Sensing Letters, 20:1–5, 2023.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Learning invariant representation via contrastive feature alignment for clutter robust sar atr.IEEE Geoscience and Remote Sensing Letters, 20:1–5, 2023

Reference 10

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Observation 6bbba32a-a8c4-44c4-9fa9-40c59500dce3 · outbound

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Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Unresolved cited work

Reference 11

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Observation 60a0745a-e75e-4aef-bd27-a15651281eb3 · outbound

This paper cites Neural expectation maximization.Advances in neural information processing systems, 30, 2017.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Neural expectation maximization.Advances in neural information processing systems, 30, 2017

Reference 12

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Observation 1480d2ac-dc07-4986-ac07-2efa183254af · outbound

This paper cites Object-centric learning with slot attention.Advances in neural information processing systems, 33:11525–11538, 2020.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Object-centric learning with slot attention.Advances in neural information processing systems, 33:11525–11538, 2020

Reference 13

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Observation c503b148-7ae4-4151-9e9f-7be8f09581d1 · outbound

This paper cites Bridging the Gap to Real-World Object-Centric Learning.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Bridging the Gap to Real-World Object-Centric Learning

Reference 14

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Observation 9fee5dfc-fec0-424f-8741-242e85e2f977 · outbound

This paper cites Invariant Slot Attention: Object Discovery with Slot-Centric Reference Frames.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Invariant Slot Attention: Object Discovery with Slot-Centric Reference Frames

Reference 15

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Observation 7a52c2bc-be80-41ec-ad53-6debcab49c1f · outbound

This paper cites Grandmother cells, symmetry, and invariance: how the term arose and what the facts suggest.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Grandmother cells, symmetry, and invariance: how the term arose and what the facts suggest

Reference 16

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Observation 1ed6e2d9-6eaa-40ca-900c-240815861efd · outbound

This paper cites Dual information purification for lightweight sar object detection.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Dual information purification for lightweight sar object detection

Reference 17

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Observation fc1086f6-a77b-481e-baf6-efefdd65b11f · outbound

This paper cites Cross-rejective open-set sar image registration.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Cross-rejective open-set sar image registration

Reference 18

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Observation 3b109815-10e1-443d-9f72-8cbda3d4ca56 · outbound

This paper cites Guided slot attention for unsupervised video object segmentation.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Guided slot attention for unsupervised video object segmentation

Reference 19

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Observation 15d0bcda-6329-4d4a-abcf-5baf1b31793f · outbound

This paper cites Parametric scattering networks.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Parametric scattering networks

Reference 20

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Observation f2e1cbc0-73c4-443f-975f-7fe01fa4a251 · outbound

This paper cites Speckle Suppression and Analysis for Synthetic Aperture Radar Images.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Speckle Suppression and Analysis for Synthetic Aperture Radar Images

Reference 21

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Observation 3ba76179-d15b-47f6-a946-91d359f32379 · outbound

This paper cites Frost, Josephine Abbott Stiles, K.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Frost, Josephine Abbott Stiles, K

Reference 22

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Observation e6d6ab23-b73d-4009-b15c-ad9fd3b6f0e1 · outbound

This paper cites Attributed scattering centers for sar atr.IEEE Transactions on image processing, 6(1):79–91, 1997.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Attributed scattering centers for sar atr.IEEE Transactions on image processing, 6(1):79–91, 1997

Reference 23

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Observation 502a56f1-eb28-480b-9233-2e026b40fcb5 · outbound

This paper cites Vsfa: Visual and scattering topological feature fusion and alignment network for unsupervised domain adaptation in sar target recognition.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Vsfa: Visual and scattering topological feature fusion and alignment network for unsupervised domain adaptation in sar target recognition

Reference 24

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Observation a1358281-aa8b-40b0-bc17-5b3a8e620fa6 · outbound

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Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Unresolved cited work

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Observation cde8f928-8603-4ed4-b1f8-caffaf054fcc · outbound

This paper cites Bottom-Up Scattering Information Perception Network for SAR target recognition.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Bottom-Up Scattering Information Perception Network for SAR target recognition

Reference 26

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Observation d060f36c-3e93-486c-b41e-b837caf58fbd · outbound

This paper cites Fusion of target and shadow regions for improved sar atr.IEEE Transactions on Geoscience and Remote Sensing, 60:1–17, 2022.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Fusion of target and shadow regions for improved sar atr.IEEE Transactions on Geoscience and Remote Sensing, 60:1–17, 2022

Reference 27

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Observation b4eb27f1-8368-43f3-8764-b628e6071577 · outbound

This paper cites Sar atr of ground vehicles based on lm-bn-cnn.IEEE Transactions on Geoscience and Remote Sensing, 56(12):7282–7293, 2018.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Sar atr of ground vehicles based on lm-bn-cnn.IEEE Transactions on Geoscience and Remote Sensing, 56(12):7282–7293, 2018

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Observation 97a10b7d-89d0-4682-ac71-06f8432b8e09 · outbound

This paper cites Bootstrapping top-down information for self-modulating slot attention.Advances in Neural Information Processing Systems, 37:103751–103773, 2024.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Bootstrapping top-down information for self-modulating slot attention.Advances in Neural Information Processing Systems, 37:103751–103773, 2024

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source=pdf_text observed=2026-08-04T19:24:39.808246Z digest=sha256:b9fbd30a6e2e1538f2f0a15d2e04faa73be99e642e4e8455428f07a25cbb96ce

Observation a903286c-f691-495d-8cd5-5fa9d0e24731 · outbound

This paper cites Toward causal representation learning.Proceedings of the IEEE, 109(5):612–634, 2021.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Toward causal representation learning.Proceedings of the IEEE, 109(5):612–634, 2021

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Observation 8648250e-973d-429e-b358-d9b6e82b0e75 · outbound

This paper cites Generalization and Robustness Implications in Object-Centric Learning.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Generalization and Robustness Implications in Object-Centric Learning

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Observation ce26ba86-d840-455c-9a17-eb819ce28b0d · outbound

This paper cites Object-Centric Slot Diffusion.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Object-Centric Slot Diffusion

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Observation 1fe79c14-632b-4a5e-88ed-eeaf8954dda8 · outbound

This paper cites Slotdiffusion: Object-centric generative modeling with diffusion models.Advances in Neural Information Processing Systems, 36:50932–50958, 2023.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Slotdiffusion: Object-centric generative modeling with diffusion models.Advances in Neural Information Processing Systems, 36:50932–50958, 2023

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Observation dddb4ecf-4b12-4742-a3c3-a06d85fbbc0c · outbound

This paper cites Improving cross-modal retrieval with set of diverse embeddings.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Improving cross-modal retrieval with set of diverse embeddings

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Observation 8b958306-12df-4d2f-af1d-21aee8fb2a3c · outbound

This paper cites Improving sound source localization with joint slot attention on image and audio.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Improving sound source localization with joint slot attention on image and audio

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Observation c3e45fdc-2f4c-416f-9340-8bdc9a825c14 · outbound

This paper cites Future Slot Prediction for Unsupervised Object Discovery in Surgical Video.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Future Slot Prediction for Unsupervised Object Discovery in Surgical Video

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source=pdf_text observed=2026-08-04T19:24:39.840342Z digest=sha256:c85f6d41061e643f3a7b2ca53e0ecd2d467c81f7a8e465a56a2c099ab148275e

Observation 0adbfa82-dc8f-4b0a-aedd-5845e68ba72d · outbound

This paper cites Conditional Object-Centric Learning from Video.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Conditional Object-Centric Learning from Video

Reference 37

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source=pdf_text observed=2026-08-04T19:24:39.845000Z digest=sha256:27d863a08376794c4796dca336e26ad1805c1ef6b341257d26cfd51d3f2a247c

Observation c1983579-c08d-4353-9bb6-cd00d85cb6a0 · outbound

This paper cites Multimodal slot vision transformer for sar image classification.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Multimodal slot vision transformer for sar image classification

Reference 38

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source=pdf_text observed=2026-08-04T19:24:39.849417Z digest=sha256:8fd23b70872ad94b7d2e6d62327a452940958af62b22a46fa4b299e7e5b81b26

Observation fcc5c59d-8bb5-4f7f-b9b3-6fcdd556636d · outbound

This paper cites Slotfusion: Object-centric audiovisual feature fusion with slot attention for remote sensing scene recognition.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Slotfusion: Object-centric audiovisual feature fusion with slot attention for remote sensing scene recognition

Reference 39

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source=pdf_text observed=2026-08-04T19:24:39.853948Z digest=sha256:0a54fa8514f2a9022282c457d098847c44df501181f8ed81ac31a695baba915c

Observation 89b9a4bd-2073-4e75-895a-3edd29c3fff8 · outbound

This paper cites Daubechies.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Daubechies

Reference 40

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source=pdf_text observed=2026-08-04T19:24:39.858728Z digest=sha256:aa7d3e0eb79495f05dd0f28835195f3cdf4cc84f19406eab6ac676c6ce6ba943

Observation 6db163fa-3e79-480a-b0eb-8106a13788b6 · outbound

This paper cites Sar image segmentation based on convolutional- wavelet neural network and markov random field.Pattern Recognition, 64:255–267, 2017.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Sar image segmentation based on convolutional- wavelet neural network and markov random field.Pattern Recognition, 64:255–267, 2017

Reference 41

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source=pdf_text observed=2026-08-04T19:24:39.863246Z digest=sha256:19583cadbd899fed708e799cff337c014db993bed68efd149b4a7f101c0e4f42

Observation e4405409-4f1b-482a-b201-0bbcf0e26f68 · outbound

This paper cites Tello, C.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Tello, C

Reference 42

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source=pdf_text observed=2026-08-04T19:24:39.867485Z digest=sha256:0fbaaa4859e0144404a2ccdea7fdd43adc4af8b513632ab95714155064ae3dcf

Observation 1947403f-ad59-4bd3-8c3c-8cfbb9289ce5 · outbound

This paper cites De Grandi, Jong-Sen Lee, and Dale L.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion De Grandi, Jong-Sen Lee, and Dale L

Reference 43

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source=pdf_text observed=2026-08-04T19:24:39.872243Z digest=sha256:8fb4055dff8c913ad6d6b89f84e4c8d78a0eed9de8926ebc6034e683b51e6413

Observation 0c0ab437-9904-4258-9529-89c9fbbf0a50 · outbound

This paper cites De Grandi, Richard M.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion De Grandi, Richard M

Reference 44

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source=pdf_text observed=2026-08-04T19:24:39.876376Z digest=sha256:364bc027a9dc49bd63b64d0cab7d2e33ac87de7c77d9870b0760eb9d51847a53

Observation f88b0b71-7d94-470b-8b37-810261ed7606 · outbound

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

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion U-net: Convolutional networks for biomedical image segmentation

Reference 45

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source=pdf_text observed=2026-08-04T19:24:39.880718Z digest=sha256:258bac399db9ce749fe00ccd05ccae69fc9d729e03f647a9f9e8c1def2c0da15

Observation c4dba303-a6aa-4449-8c2d-c48c8c13bd09 · outbound

This paper cites Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Reference 46

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source=pdf_text observed=2026-08-04T19:24:39.885117Z digest=sha256:467871d5b154b84c8b2549963a6a6b64065b26ae06ece79ef736ad14881024fc

Observation 007e7d77-8e43-488a-9a4c-a28dd4985a6d · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Adam: A Method for Stochastic Optimization

Reference 47

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source=pdf_text observed=2026-08-04T19:24:39.889725Z digest=sha256:c9469ed178f847e0f3e60fb7bf1b6ad403643a728bf6fe095632ba9c57860877

Observation bf5f5831-113e-4ebc-be0c-58225de6a9f9 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion DINOv2: Learning Robust Visual Features without Supervision

Reference 48

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source=pdf_text observed=2026-08-04T19:24:39.894167Z digest=sha256:fadd3b527843648b116fdde7aa4633d5479c9afcb7a7faf53998a04c10147fd7

Observation ed8c575f-5481-4a16-af20-e2b41697dea8 · outbound

This paper cites Visualizing data using t-sne.Journal of machine learning research, 9(Nov):2579–2605, 2008.

Learning Object-Centric Representations in SAR Images with Multi-Level Feature Fusion Visualizing data using t-sne.Journal of machine learning research, 9(Nov):2579–2605, 2008

Reference 49

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source=pdf_text observed=2026-08-04T19:24:39.898595Z digest=sha256:91e6ebc9b4c3058b41ee04e9692e17bb7e67be624b246f8ec1fa6152da8be5d3

Pith citing papers

No inbound Pith citation observations are available.