Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation | Paper Citation Record

Observation 0401568c-8459-4a2d-8744-0f6ffbdde0d0 · outbound

This paper cites Emotion recognition in speech using cross- modal transfer in the wild.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Emotion recognition in speech using cross- modal transfer in the wild

Reference 1

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Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Wasserstein generative adversarial networks

Reference 2

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This paper cites Synthetic Data from Diffusion Models Improves ImageNet Classification.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Synthetic Data from Diffusion Models Improves ImageNet Classification

Reference 3

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This paper cites Label-Efficient Semantic Segmentation with Diffusion Models.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Label-Efficient Semantic Segmentation with Diffusion Models

Reference 4

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Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Unresolved cited work

Reference 5

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This paper cites Data-free learning of student networks.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Data-free learning of student networks

Reference 6

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This paper cites GeoDiffusion: Text-Prompted Geometric Control for Object Detection Data Generation.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation GeoDiffusion: Text-Prompted Geometric Control for Object Detection Data Generation

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This paper cites Encoder-decoder with atrous separable convolution for semantic image segmentation.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Encoder-decoder with atrous separable convolution for semantic image segmentation

Reference 8

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This paper cites Distilling knowledge via knowledge review.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Distilling knowledge via knowledge review

Reference 9

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This paper cites On the Importance of Noise Scheduling for Diffusion Models.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation On the Importance of Noise Scheduling for Diffusion Models

Reference 10

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This paper cites A generalist framework for panoptic segmen- tation of images and videos.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation A generalist framework for panoptic segmen- tation of images and videos

Reference 11

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This paper cites an unresolved cited work.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Unresolved cited work

Reference 12

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

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Masked-attention mask transformer for universal image segmentation

Reference 13

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This paper cites Speckle noise reduction technique for sar images using statistical characteristics of speckle noise and discrete wavelet transform.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Speckle noise reduction technique for sar images using statistical characteristics of speckle noise and discrete wavelet transform

Reference 14

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This paper cites MMYOLO: OpenMMLab YOLO series toolbox and benchmark.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation MMYOLO: OpenMMLab YOLO series toolbox and benchmark

Reference 15

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This paper cites an unresolved cited work.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Unresolved cited work

Reference 16

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This paper cites Oil-spill-response-oriented in- formation products derived from a rapid-repeat time series of sar images.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Oil-spill-response-oriented in- formation products derived from a rapid-repeat time series of sar images

Reference 17

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This paper cites Up to 100$\times$ Faster Data-free Knowledge Distillation.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Up to 100$\times$ Faster Data-free Knowledge Distillation

Reference 18

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This paper cites Data augmentation for object detec- tion via controllable diffusion models.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Data augmentation for object detec- tion via controllable diffusion models

Reference 19

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This paper cites DreamDA: Generative Data Augmentation with Diffusion Models.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation DreamDA: Generative Data Augmentation with Diffusion Models

Reference 20

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This paper cites Gemme and S.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Gemme and S

Reference 21

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Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Generative adversarial networks

Reference 22

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Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Class attention transfer based knowledge distillation

Reference 23

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This paper cites Gans trained by a two time-scale update rule converge to a local nash equilib- rium.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Gans trained by a two time-scale update rule converge to a local nash equilib- rium

Reference 24

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This paper cites Distilling the Knowledge in a Neural Network.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Distilling the Knowledge in a Neural Network

Reference 25

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This paper cites Denoising dif- fusion probabilistic models.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Denoising dif- fusion probabilistic models

Reference 26

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This paper cites Segment any- thing.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Segment any- thing

Reference 27

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This paper cites Konik and K.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Konik and K

Reference 28

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Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Anatomically-controllable medical image gen- eration with segmentation-guided diffusion models

Reference 29

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This paper cites Krestenitis, G.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Krestenitis, G

Reference 30

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Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Unresolved cited work

Reference 31

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Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Semantic segmentation with generative models: Semi-supervised learning and strong out-of-domain generalization

Reference 32

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Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Online knowledge distillation for efficient pose estimation

Reference 33

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Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Is Synthetic Data From Diffusion Models Ready for Knowledge Distillation?

Reference 34

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Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Structured knowledge distillation for semantic segmentation

Reference 35

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Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Decoupled Weight Decay Regularization

Reference 36

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This paper cites Nieto-Hidalgo, A.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Nieto-Hidalgo, A

Reference 37

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Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Relational knowledge distillation

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Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation High-resolution image synthesis with latent diffusion models

Reference 39

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Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Unresolved cited work

Reference 40

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This paper cites Salberg, O.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Salberg, O

Reference 41

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This paper cites Generative data augmentation improves scribble-supervised semantic segmentation.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Generative data augmentation improves scribble-supervised semantic segmentation

Reference 42

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This paper cites Enhancing oil spill detection using synthetic aperture radar with dual attention u-net model.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Enhancing oil spill detection using synthetic aperture radar with dual attention u-net model

Reference 43

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Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Unresolved cited work

Reference 44

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This paper cites Analysis and effects of speckle noise in sar images.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Analysis and effects of speckle noise in sar images

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.673110Z

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Observation fe5387ef-7caa-4181-8cbc-430260dc8eb7 · outbound

This paper cites Denoising Diffusion Implicit Models.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Denoising Diffusion Implicit Models

Reference 46

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This paper cites Sudre, Wenqi Li, Tom Vercauteren, Sebastien Ourselin, and M.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Sudre, Wenqi Li, Tom Vercauteren, Sebastien Ourselin, and M

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.661683Z

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Observation 5d99bf5d-b16b-4c08-a857-2ecef742cbbc · outbound

This paper cites Rethinking the inception ar- chitecture for computer vision.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Rethinking the inception ar- chitecture for computer vision

Reference 48

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Observation 7cc53ed4-a826-4af0-a507-e650f476cdeb · outbound

This paper cites Wan Yusof.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Wan Yusof

Reference 49

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Observation 4bf7ed60-58f8-441e-8dc2-ffbf1d00702d · outbound

This paper cites Cross-modal knowledge distillation for action recognition.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Cross-modal knowledge distillation for action recognition

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.629056Z

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Observation 5680d710-1140-4c5d-8c36-bc720ccfa4be · outbound

This paper cites Diffuse attend and segment: Un- supervised zero-shot segmentation using stable diffusion.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Diffuse attend and segment: Un- supervised zero-shot segmentation using stable diffusion

Reference 51

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Observation cd3fc8b6-2d3a-4e49-9e0b-f890e58b00c2 · outbound

This paper cites Satsynth: Augmenting image-mask pairs through diffusion models for aerial semantic segmentation.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Satsynth: Augmenting image-mask pairs through diffusion models for aerial semantic segmentation

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.611667Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation eb04d9b7-fa8f-4947-adb2-3ef0a381a69c · outbound

This paper cites Effective Data Augmentation With Diffusion Models.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Effective Data Augmentation With Diffusion Models

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-11T18:18:13.047022Z

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Observation 90276418-9ac8-4326-b36a-b1d6a9a8e253 · outbound

This paper cites Similarity-preserving knowl- edge distillation.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Similarity-preserving knowl- edge distillation

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.600293Z

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Observation 005a82a5-c3e5-4420-a3f1-e06172c1fbf9 · outbound

This paper cites Vespe and H.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Vespe and H

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.589459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e7733b8d-378d-41d1-bbc2-de0d07b46e91 · outbound

This paper cites What makes a ”good” data augmentation in knowledge dis- tillation - a statistical perspective.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation What makes a ”good” data augmentation in knowledge dis- tillation - a statistical perspective

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.578296Z

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Observation c7f4eb9c-b834-4677-a256-69cf22e0fc69 · outbound

This paper cites an unresolved cited work.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Unresolved cited work

Reference 57

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:18:13.567315Z

Source-reported events for the cited work

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Observation 053edc9d-b5c2-45fa-a521-83550f1c9867 · outbound

This paper cites Intra-class feature variation distillation for se- mantic segmentation.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Intra-class feature variation distillation for se- mantic segmentation

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.556494Z

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Observation ffdb5491-0d98-4f8d-9548-b6019deafb1c · outbound

This paper cites Scaled decoupled distillation.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Scaled decoupled distillation

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.544233Z

Source-reported events for the cited work

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Observation 66725c2a-23ff-4233-a5f2-e3989613d62b · outbound

This paper cites Diffumask: Synthesizing images with pixel-level annotations for semantic segmentation using dif- fusion models.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Diffumask: Synthesizing images with pixel-level annotations for semantic segmentation using dif- fusion models

Reference 60

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Observation d8ff77df-0746-4a4d-881f-c5f3d1e9fef0 · outbound

This paper cites Compositional oil spill detection based on object detector and adapted segment anything model from sar images.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Compositional oil spill detection based on object detector and adapted segment anything model from sar images

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.526395Z

Source-reported events for the cited work

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Observation c59f60cc-c49d-4908-8f5e-45317001a767 · outbound

This paper cites Segformer: Simple and efficient design for semantic segmentation with transform- ers.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Segformer: Simple and efficient design for semantic segmentation with transform- ers

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.514426Z

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Observation e2e6fc15-6c00-46af-8591-2992c6bdbd4a · outbound

This paper cites Data-free knowledge amalgamation via group-stack dual- gan.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Data-free knowledge amalgamation via group-stack dual- gan

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.503198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8d48b286-109d-4b5b-b70d-28790212c1f8 · outbound

This paper cites Diffusion-based data augmentation for nuclei image segmentation.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Diffusion-based data augmentation for nuclei image segmentation

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.490293Z

Source-reported events for the cited work

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Observation 7a3c3353-c53f-4aad-8942-622e04ced841 · outbound

This paper cites Paying more at- tention to attention: Improving the performance of convolu- tional neural networks via attention transfer.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Paying more at- tention to attention: Improving the performance of convolu- tional neural networks via attention transfer

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.477768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation be188da6-3cd0-4aea-846c-bec60b6b1acb · outbound

This paper cites Fast human pose estimation.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Fast human pose estimation

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.466796Z

Source-reported events for the cited work

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Observation 9bdabc5f-f214-4dcd-aaf9-c665c923c4bf · outbound

This paper cites Oil spill detection in quad-polarimetric sar images using an advanced convolutional neural network based on super- pixel model.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Oil spill detection in quad-polarimetric sar images using an advanced convolutional neural network based on super- pixel model

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.456211Z

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Observation c9df4709-edc2-41ad-89da-2847d60aad14 · outbound

This paper cites Joint- net: Extending text-to-image diffusion for dense distribution modeling.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Joint- net: Extending text-to-image diffusion for dense distribution modeling

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.445209Z

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Observation 7f695895-7450-473c-bd56-e271585943b9 · outbound

This paper cites DiffusionEngine: Diffusion Model is Scalable Data Engine for Object Detection.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation DiffusionEngine: Diffusion Model is Scalable Data Engine for Object Detection

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-11T18:18:13.114001Z

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Observation 372787df-559a-416b-b0ea-6c4bced782f3 · outbound

This paper cites Decoupled knowledge distillation.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Decoupled knowledge distillation

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.433805Z

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Observation 1404960a-c5c1-4a2a-ae0e-35e8ded56254 · outbound

This paper cites Through-wall human pose estimation using radio signals.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Through-wall human pose estimation using radio signals

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.420729Z

Source-reported events for the cited work

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Observation 1dd566e2-980d-44c6-a033-91a6044fa416 · outbound

This paper cites Build- ing extraction from high spatial resolution remote sensing images via multiscale-aware and segmentation-prior condi- tional random fields.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Build- ing extraction from high spatial resolution remote sensing images via multiscale-aware and segmentation-prior condi- tional random fields

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.407985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 32b00c85-caaf-49e9-b1b1-44cb8f6df180 · outbound

This paper cites A spectral-spatial-dependent global learning framework for insufficient and imbalanced hyperspectral image classi- fication.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation A spectral-spatial-dependent global learning framework for insufficient and imbalanced hyperspectral image classi- fication

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.394760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f8317006-5c22-4c4a-851e-44ad21a7a89f · outbound

This paper cites A global context-aware and batch-independent network for road extraction from vhr satellite imagery.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation A global context-aware and batch-independent network for road extraction from vhr satellite imagery

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.383561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3b464400-a0be-4229-8220-741aa02d3b5f · outbound

This paper cites Oil spill contextual and boundary-supervised detection network based on marine sar images.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Oil spill contextual and boundary-supervised detection network based on marine sar images

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.373031Z

Source-reported events for the cited work

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Observation c8ef77c5-b9c1-4c41-ad74-f0c44ed2b3c1 · outbound

This paper cites We utilize a linear noise sched- uler with 1, 000 steps for training, while we use the DDIM.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation We utilize a linear noise sched- uler with 1, 000 steps for training, while we use the DDIM

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.361512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5364be2d-b153-4bba-8889-0a2ad9396204 · outbound

This paper cites Training is con- ducted on a Nvidia A6000 GPU.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Training is con- ducted on a Nvidia A6000 GPU

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.350834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1bdeda74-1a7e-4433-8a43-a36069ffd0ae · outbound

This paper cites 8 SAR image GTDeepLabV3+ DeepLabV3+ w/ DAKTer SAR image GTMask2Former Mask2Former w/ DAKTer SAR image GTCBDNet CBDNet w/ DAKTer SAR image GTSegFormer SegFormer w/ DAKTer Figure 12.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation 8 SAR image GTDeepLabV3+ DeepLabV3+ w/ DAKTer SAR image GTMask2Former Mask2Former w/ DAKTer SAR image GTCBDNet CBDNet w/ DAKTer SAR image GTSegFormer SegFormer w/ DAKTer Figure 12

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:18:13.328629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation efe15ff9-865b-4c6d-8294-0937e19ab479 · outbound

This paper cites an unresolved cited work.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Unresolved cited work

Reference 80

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:18:13.316701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 19e0d6ed-8d86-451e-84db-50a8fb89cdc7 · outbound

This paper cites an unresolved cited work.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation Unresolved cited work

Reference 256

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:18:13.340927Z

Source-reported events for the cited work

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