A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning | Paper Citation Record

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This paper cites An empirical study of remote sensing pretraining,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning An empirical study of remote sensing pretraining,

Reference 1

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Observation 99e7532e-52a2-4564-825b-d65472b0d3cc · outbound

This paper cites Advancing plain vision transformer toward remote sensing foundation model,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Advancing plain vision transformer toward remote sensing foundation model,

Reference 2

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This paper cites Mtp: Advancing remote sensing foundation model via multi-task pretraining,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Mtp: Advancing remote sensing foundation model via multi-task pretraining,

Reference 3

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Observation 0b99b3bd-7bbc-44f9-bb5d-f0845a8f5852 · outbound

This paper cites Simmim: A simple framework for masked image modeling,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Simmim: A simple framework for masked image modeling,

Reference 4

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Observation 60c2bb29-5f23-44ec-b84b-d65810153b70 · outbound

This paper cites Dense contrastive learning for self-supervised visual pre-training,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Dense contrastive learning for self-supervised visual pre-training,

Reference 5

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Observation dfc7c2e5-f453-47ea-9c38-ece79f267ee4 · outbound

This paper cites Ringmo: A remote sensing foundation model with masked image modeling,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Ringmo: A remote sensing foundation model with masked image modeling,

Reference 6

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Observation 81fc7c90-acc8-45c4-af08-bd1dbccd8db4 · outbound

This paper cites Scale-mae: A scale-aware masked autoencoder for multiscale geospatial representation learning,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Scale-mae: A scale-aware masked autoencoder for multiscale geospatial representation learning,

Reference 7

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Observation 580ea666-6f5e-4c20-b34d-3efa6b351136 · outbound

This paper cites SpectralGPT: Spectral Remote Sensing Foundation Model.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning SpectralGPT: Spectral Remote Sensing Foundation Model

Reference 8

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Observation 6c663cf6-17de-49ab-adb3-bb542407cbad · outbound

This paper cites Scattering prompt tuning: A fine-tuned foundation model for sar object recognition,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Scattering prompt tuning: A fine-tuned foundation model for sar object recognition,

Reference 10

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This paper cites Croma: Remote sensing represen- tations with contrastive radar-optical masked autoencoders,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Croma: Remote sensing represen- tations with contrastive radar-optical masked autoencoders,

Reference 11

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Observation c90fdbb0-b5f3-4474-b150-741e6d13288c · outbound

This paper cites Deep learning meets sar: Concepts, models, pitfalls, and perspectives,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Deep learning meets sar: Concepts, models, pitfalls, and perspectives,

Reference 12

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Observation 6954690f-23ac-4b66-b086-870e130ba375 · outbound

This paper cites Mcanet: A joint semantic segmentation framework of optical and sar images for land use classification,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Mcanet: A joint semantic segmentation framework of optical and sar images for land use classification,

Reference 13

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Observation 29f86020-acd4-49b5-bc43-9a7f071d533b · outbound

This paper cites Denet: Double- encoder network with feature refinement and region adaption for terrain segmentation in polsar images,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Denet: Double- encoder network with feature refinement and region adaption for terrain segmentation in polsar images,

Reference 14

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Observation c2c46261-914c-48c3-affb-63559c75e38c · outbound

This paper cites Sar automatic target recognition method based on multi-stream complex-valued networks,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Sar automatic target recognition method based on multi-stream complex-valued networks,

Reference 15

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This paper cites Interpretable deep learning: Interpretation, interpretability, trustworthi- ness, and beyond,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Interpretable deep learning: Interpretation, interpretability, trustworthi- ness, and beyond,

Reference 16

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Observation 2978c543-79ee-4e00-987d-496b25d0ba80 · outbound

This paper cites Four- component scattering model for polarimetric sar image decomposition,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Four- component scattering model for polarimetric sar image decomposition,

Reference 17

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Observation 8d2d4435-683d-4b77-984d-7f5a81f21280 · outbound

This paper cites A review of target decomposition theorems in radar polarimetry,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning A review of target decomposition theorems in radar polarimetry,

Reference 18

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Observation 3ecc66b2-75b1-453c-b881-63692d539b18 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning LLaMA: Open and Efficient Foundation Language Models

Reference 19

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Observation 2919192d-42dc-4a4f-9d74-0ddfe730556f · outbound

This paper cites Masked autoencoders are scalable vision learners,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Masked autoencoders are scalable vision learners,

Reference 20

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This paper cites Segment anything,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Segment anything,

Reference 21

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This paper cites Satmae: Pre-training transformers for temporal and multi-spectral satellite imagery,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Satmae: Pre-training transformers for temporal and multi-spectral satellite imagery,

Reference 22

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Observation a6530437-0753-4932-9e4e-0326bc8c81a0 · outbound

This paper cites Feature Guided Masked Autoencoder for Self-supervised Learning in Remote Sensing.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Feature Guided Masked Autoencoder for Self-supervised Learning in Remote Sensing

Reference 23

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Observation b49f1f04-9fcc-4151-8e64-78e7f71deee6 · outbound

This paper cites Self-supervised vision transformers for joint sar-optical representation learning,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Self-supervised vision transformers for joint sar-optical representation learning,

Reference 24

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This paper cites Skysense: A multi-modal remote sensing foundation model towards universal interpretation for earth observation imagery,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Skysense: A multi-modal remote sensing foundation model towards universal interpretation for earth observation imagery,

Reference 25

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This paper cites Polarimetric convo- lutional network for polsar image classification,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Polarimetric convo- lutional network for polsar image classification,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.994622Z

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This paper cites Radar polaritnetry for geoscience applica- tions,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Radar polaritnetry for geoscience applica- tions,

Reference 27

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Observation f54a3374-8889-42e3-820f-f311cfebc8cd · outbound

This paper cites New decomposition of the radar target scattering matrix,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning New decomposition of the radar target scattering matrix,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.965232Z

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Observation 162cf495-c614-446c-ab5c-5da5ab5ac946 · outbound

This paper cites Simulated polari- metric signatures of primitive geometrical shapes,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Simulated polari- metric signatures of primitive geometrical shapes,

Reference 29

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Observation 1b6ed29d-4b8e-411b-8423-dc426e27866e · outbound

This paper cites A review of polarimetry in the context of synthetic aperture radar: Concepts and information extraction,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning A review of polarimetry in the context of synthetic aperture radar: Concepts and information extraction,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.933853Z

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Observation 19992abc-e9d3-4655-a4fd-36305d4dd611 · outbound

This paper cites Eigen-decomposition-based four-component decomposition for polsar data,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Eigen-decomposition-based four-component decomposition for polsar data,

Reference 31

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Observation a74d0b93-0914-49db-ad48-a9e0060ec0ab · outbound

This paper cites Advanced polarimetric target decomposition,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Advanced polarimetric target decomposition,

Reference 32

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Observation 5e8f4ab9-eae7-42ac-a0ab-fa9daaef6cb7 · outbound

This paper cites Phenomenological theory of radar targets,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Phenomenological theory of radar targets,

Reference 33

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Observation b6a7f434-362f-47fd-9ecd-e3ed9b167ade · outbound

This paper cites Three-component scattering model to describe polarimetric sar data,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Three-component scattering model to describe polarimetric sar data,

Reference 34

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Observation c466951a-48b3-49e2-9367-3838dcd7afba · outbound

This paper cites Seven-component scattering power decomposition of polsar coherency matrix,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Seven-component scattering power decomposition of polsar coherency matrix,

Reference 35

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Observation 74f791ab-ee22-430e-9951-a77b74a0c70c · outbound

This paper cites Exploring fine polarimetric decomposition technique for built-up area monitoring,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Exploring fine polarimetric decomposition technique for built-up area monitoring,

Reference 36

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Observation 558d2ee3-1058-4bd9-ba9a-5f6eaa03eac3 · outbound

This paper cites Polarimetric decomposition-based unified manmade target scattering characterization with mathematical programming strategies,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Polarimetric decomposition-based unified manmade target scattering characterization with mathematical programming strategies,

Reference 37

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Observation 27b86f30-9325-43bf-9eaa-7f516236671f · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 38

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This paper cites Pyramid scene parsing network,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Pyramid scene parsing network,

Reference 39

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Observation b446a72f-7891-43d8-a343-c158133ae0cb · outbound

This paper cites Unified perceptual parsing for scene understanding,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Unified perceptual parsing for scene understanding,

Reference 40

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Observation b0869c45-63ce-4c18-9454-426b87e5799d · outbound

This paper cites Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

Reference 41

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Observation e19ce224-f0f9-4e18-9929-207c37266fd2 · outbound

This paper cites Asymmetric non-local neural networks for semantic segmentation,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Asymmetric non-local neural networks for semantic segmentation,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.766976Z

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Observation 2abb4ec1-d27d-4407-a2c4-53c1ac0b3da8 · outbound

This paper cites Ccnet: Criss-cross attention for semantic segmentation,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Ccnet: Criss-cross attention for semantic segmentation,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.751954Z

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Observation e111f3c2-6aa8-4cd5-bc73-ab3571e3317e · outbound

This paper cites K-net: Towards unified image segmentation,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning K-net: Towards unified image segmentation,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.737684Z

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Observation 0d8e554b-7f3a-4835-b71b-ede6f8c5fd55 · outbound

This paper cites SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation

Reference 45

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Observation 8a7b2cf7-2374-4f35-b899-5957e76845f9 · outbound

This paper cites Masked-attention mask transformer for universal image segmentation,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Masked-attention mask transformer for universal image segmentation,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.722999Z

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Observation cddf3852-50cd-4a04-afcb-23f266711584 · outbound

This paper cites Deep dual-resolution networks for real-time and accurate semantic segmentation of traffic scenes,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Deep dual-resolution networks for real-time and accurate semantic segmentation of traffic scenes,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.709638Z

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Observation bc13ec6e-912f-413f-9e6d-9db0b996b76b · outbound

This paper cites Agmtr: Agent mining transformer for few-shot segmentation in remote sensing,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Agmtr: Agent mining transformer for few-shot segmentation in remote sensing,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.692962Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 28192313-ee6c-4376-9b09-54a67e6bc31d · outbound

This paper cites Not just learning from others but relying on yourself: A new perspective on few-shot segmentation in remote sensing,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Not just learning from others but relying on yourself: A new perspective on few-shot segmentation in remote sensing,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.674743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0b995866-b988-4b23-bf15-febd57a96665 · outbound

This paper cites Hrsid: A high-resolution sar images dataset for ship detection and instance segmentation,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Hrsid: A high-resolution sar images dataset for ship detection and instance segmentation,

Reference 50

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Observation 88d1a786-ae7c-4144-a65a-bb55f58d2175 · outbound

This paper cites Air-polsar-seg: A large- scale data set for terrain segmentation in complex-scene polsar images,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Air-polsar-seg: A large- scale data set for terrain segmentation in complex-scene polsar images,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.635103Z

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Observation fe5b095c-3598-4454-b78e-979fda219f5e · outbound

This paper cites Mask r-cnn,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Mask r-cnn,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.619147Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 772ac7a9-d05a-4483-b3d3-0f6b93500e46 · outbound

This paper cites Cascade r-cnn: Delving into high quality object detection,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Cascade r-cnn: Delving into high quality object detection,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.602588Z

Source-reported events for the cited work

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Observation 1fdc90ca-e0a1-4a8a-9ffd-913178fb5b77 · outbound

This paper cites Tood: Task- aligned one-stage object detection,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Tood: Task- aligned one-stage object detection,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.566130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bb31cb64-54e7-4f42-81b3-685885bab7e2 · outbound

This paper cites Swin-paff: A sar ship detection network with contextual cross-information fusion.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Swin-paff: A sar ship detection network with contextual cross-information fusion

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.552471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 68741ac9-f0eb-4c5f-9d37-3d39e7512d08 · outbound

This paper cites A novel anchor- free detector using global context-guide feature balance pyramid and united attention for sar ship detection,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning A novel anchor- free detector using global context-guide feature balance pyramid and united attention for sar ship detection,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.538417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 37c21048-6dcf-4a4b-9829-84d3b36e3054 · outbound

This paper cites Dense distinct query for end-to-end object detection,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Dense distinct query for end-to-end object detection,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.521056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f71cbf4b-97d2-46f6-84ce-9cdf8f88c725 · outbound

This paper cites YOLOX: Exceeding YOLO Series in 2021.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning YOLOX: Exceeding YOLO Series in 2021

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:56.082234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e860568e-c44a-42e3-9247-ae4db2b613f1 · outbound

This paper cites Sar-aircraft-1.0: High-resolution sar aircraft detection and recognition dataset,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Sar-aircraft-1.0: High-resolution sar aircraft detection and recognition dataset,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.649985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 74dfa6fc-3550-46ed-9c76-536ef383151f · outbound

This paper cites Scattering-keypoint-guided network for oriented ship detection in high-resolution and large-scale sar images,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Scattering-keypoint-guided network for oriented ship detection in high-resolution and large-scale sar images,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.507858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a289abb9-8a16-4f5b-91f6-c0620552e41a · outbound

This paper cites Yolov5 by ultralytics,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Yolov5 by ultralytics,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.492817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8d586631-9a72-4e6c-8b2a-03e6be6ffd0c · outbound

This paper cites Mlsdnet: Multi-class lightweight sar detection network based on adaptive scale distribution attention,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Mlsdnet: Multi-class lightweight sar detection network based on adaptive scale distribution attention,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.472102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ff9d2461-e365-40ba-b608-420f21ada343 · outbound

This paper cites Diffusiondet: Diffusion model for object detection,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Diffusiondet: Diffusion model for object detection,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.453909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bb01dd99-d1ac-4527-8940-972a8aa011b0 · outbound

This paper cites Diffdet4sar: Diffusion-based aircraft target detection network for sar images,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Diffdet4sar: Diffusion-based aircraft target detection network for sar images,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.435781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4b80170e-9442-4420-971c-4237a93931bc · outbound

This paper cites SARATR-X: Toward Building A Foundation Model for SAR Target Recognition.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning SARATR-X: Toward Building A Foundation Model for SAR Target Recognition

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:56.112299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa01c828-2ae4-43b0-acdc-f5e89892c2e6 · outbound

This paper cites Unleashing channel potential: Space-frequency selection convolution for sar object detection,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Unleashing channel potential: Space-frequency selection convolution for sar object detection,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.419402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 737251df-dd1f-455a-a0f3-997d5a767802 · outbound

This paper cites Non-local neural net- works,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Non-local neural net- works,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.399788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d659396a-6c0b-4fe4-b740-a8ebd515117f · outbound

This paper cites Expectation- maximization attention networks for semantic segmentation,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Expectation- maximization attention networks for semantic segmentation,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.373892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ca3adb98-fa9b-4318-a333-d0a382900974 · outbound

This paper cites Object-level semantic segmentation on the high-resolution gaofen-3 fusar-map dataset,.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning Object-level semantic segmentation on the high-resolution gaofen-3 fusar-map dataset,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:56.351569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 601d12a2-2df1-412f-9b49-cdcaf4b3b7f2 · outbound

This paper cites SAFE: a SAR Feature Extractor based on self-supervised learning and masked Siamese ViTs.

A Complex-valued SAR Foundation Model Based on Physically Inspired Representation Learning SAFE: a SAR Feature Extractor based on self-supervised learning and masked Siamese ViTs

Reference 71

Resolution: verified exact; local_arxiv, observed 2026-08-16T12:40:56.196487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Reference resolution

Outbound references

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