Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations | Paper Citation Record

Observation 9e3c59fd-0df0-4ab0-a540-93d75974c46d · outbound

This paper cites Occluded prohibited items detection: An X-ray security inspection benchmark and de-occlusion attention module,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Occluded prohibited items detection: An X-ray security inspection benchmark and de-occlusion attention module,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.890378Z

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Observation 5eb79921-e472-40fb-a676-1112cac7eb14 · outbound

This paper cites SIXray: A large-scale security inspection X-ray benchmark for prohibited item discovery in overlapping images,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations SIXray: A large-scale security inspection X-ray benchmark for prohibited item discovery in overlapping images,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.879216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation aa906096-0b6d-482b-a07a-94df093eea78 · outbound

This paper cites PIDray: A large-scale X-ray benchmark for real-world prohibited item detection,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations PIDray: A large-scale X-ray benchmark for real-world prohibited item detection,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.867291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0a618cde-903e-42d0-9782-561aca7b1ed9 · outbound

This paper cites Towards real-world X-ray security inspection: A high-quality benchmark and lateral inhibition module for prohibited items detection,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Towards real-world X-ray security inspection: A high-quality benchmark and lateral inhibition module for prohibited items detection,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.854510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 420a233e-82a5-47cf-aeff-dfaaa79f3cf8 · outbound

This paper cites ‘unex- pected item in the bagging area’: Anomaly detection in X-ray security images,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations ‘unex- pected item in the bagging area’: Anomaly detection in X-ray security images,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.841429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation cf7b32d3-d5c3-4d50-87dd-49a437c4903c · outbound

This paper cites Toward dual- view X-ray baggage inspection: A large-scale benchmark and adaptive hierarchical cross refinement for prohibited item discovery,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Toward dual- view X-ray baggage inspection: A large-scale benchmark and adaptive hierarchical cross refinement for prohibited item discovery,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.829306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 10471849-b523-49c8-8e8b-033e30129c44 · outbound

This paper cites Dual- mode learning for multi-dataset X-ray security image detection,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Dual- mode learning for multi-dataset X-ray security image detection,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.817937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation dbcd6dd1-2372-4ea2-82a4-f305eeb85bd2 · outbound

This paper cites DivideMix: Learning with noisy labels as semi-supervised learning,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations DivideMix: Learning with noisy labels as semi-supervised learning,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.806393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ad2b9009-b6d7-4f1d-afd1-94265a2ba266 · outbound

This paper cites Co-teaching: Robust training of deep neural networks with extremely noisy labels,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Co-teaching: Robust training of deep neural networks with extremely noisy labels,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.794342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bdb4cbea-8284-4ad4-9c39-be115ec9118c · outbound

This paper cites Symmetric cross entropy for robust learning with noisy labels,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Symmetric cross entropy for robust learning with noisy labels,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.781829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e6d37d57-0f11-4a14-ac2d-c643eb0abb6d · outbound

This paper cites Training object detectors with noisy data,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Training object detectors with noisy data,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.767931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b8778ab5-d333-4c3c-9f6a-a1097db7751b · outbound

This paper cites Towards Noise-resistant Object Detection with Noisy Annotations.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Towards Noise-resistant Object Detection with Noisy Annotations

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-10T22:26:29.091195Z

Source-reported events for the cited work

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Observation 7d0de172-d195-4ec7-9c58-fd36eaee5921 · outbound

This paper cites Learning with noisy class labels for instance segmentation,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Learning with noisy class labels for instance segmentation,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.754806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2ac35811-5b60-4afd-bf1c-80c387139ec3 · outbound

This paper cites Robust object detection with inaccurate bounding boxes,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Robust object detection with inaccurate bounding boxes,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.742745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 715fce92-b4bc-43dd-8e7f-63de348d8766 · outbound

This paper cites Narrowing the gap: Improved detector training with noisy location annotations,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Narrowing the gap: Improved detector training with noisy location annotations,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.728971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d815699b-f7f5-4d80-8cc3-5a0204fbf262 · outbound

This paper cites Understand- ing deep learning requires rethinking generalization,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Understand- ing deep learning requires rethinking generalization,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.711459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 16a06d0c-00cf-44c0-9d84-f5ea76cfcb93 · outbound

This paper cites A closer look at memorization in deep networks,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations A closer look at memorization in deep networks,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.696310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4704f56e-064c-4fcb-a4f1-d4a79648c1db · outbound

This paper cites Microsoft COCO: Common objects in context,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Microsoft COCO: Common objects in context,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.683337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e1af3cb5-7eb4-4024-86fe-0e6c4d05e723 · outbound

This paper cites Detecting overlapped objects in X-ray security imagery by a label-aware mechanism,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Detecting overlapped objects in X-ray security imagery by a label-aware mechanism,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.670685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b9f587ee-36b9-4479-83e8-5dd2a97e7aeb · outbound

This paper cites Exploiting foreground and background separation for prohibited item detection in overlapping x-ray images,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Exploiting foreground and background separation for prohibited item detection in overlapping x-ray images,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.657257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 43fa4dc5-4b79-4ea7-ad8b-85581a32180b · outbound

This paper cites Baggage threat recognition using deep low-rank broad learning detec- tor,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Baggage threat recognition using deep low-rank broad learning detec- tor,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.642455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1a3a46a5-142e-48d1-ac5d-68c30259006f · outbound

This paper cites Towards automatic threat detection: A survey of advances of deep learning within x-ray security imaging,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Towards automatic threat detection: A survey of advances of deep learning within x-ray security imaging,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.627863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1e527299-df8d-4c30-8c4d-36f584cc362f · outbound

This paper cites Computer vision on x-ray data in industrial production and security applications: A comprehensive survey,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Computer vision on x-ray data in industrial production and security applications: A comprehensive survey,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.614760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 30fc8466-007b-428e-bb7f-b8d9115ab210 · outbound

This paper cites Recent advances in baggage threat detection: A comprehensive and systematic survey,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Recent advances in baggage threat detection: A comprehensive and systematic survey,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.598404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a886cf68-4acc-4d1c-8b1a-347e1e4daab0 · outbound

This paper cites Gadet: A geometry-aware x-ray prohibited items detector,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Gadet: A geometry-aware x-ray prohibited items detector,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.584955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e0c49723-fc4f-41e6-b298-28d9365c407a · outbound

This paper cites Improved Regularization of Convolutional Neural Networks with Cutout.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Improved Regularization of Convolutional Neural Networks with Cutout

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T22:26:28.792550Z

Source-reported events for the cited work

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Observation 9d2285ca-e6f0-4bc5-b78a-bd4c811cceb1 · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations mixup: Beyond Empirical Risk Minimization

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T22:26:28.797017Z

Source-reported events for the cited work

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Observation a787644c-3216-4d65-bb26-7f9ce19fb993 · outbound

This paper cites Alignmixup: Improving representations by interpolating aligned features,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Alignmixup: Improving representations by interpolating aligned features,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.572340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 68abf31a-093e-413c-8de9-049be261f9b3 · outbound

This paper cites YOLOv4: Optimal Speed and Accuracy of Object Detection.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations YOLOv4: Optimal Speed and Accuracy of Object Detection

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T22:26:28.805169Z

Source-reported events for the cited work

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Observation e4eb0610-22e0-4e6d-82b6-e6ce519195db · outbound

This paper cites Channel augmentation for visible- infrared re-identification,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Channel augmentation for visible- infrared re-identification,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.558566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation edde3068-f1da-4f26-8550-45df118d4e52 · outbound

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

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Learning transferable visual models from natural language supervision,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.538689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7e5c490b-f9ef-42c3-b262-2da776abb716 · outbound

This paper cites Adding conditional control to text-to-image diffusion models,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Adding conditional control to text-to-image diffusion models,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.523518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c9319467-d460-4972-8508-7bf9e3e86dd4 · outbound

This paper cites Data augmentation for object detection via controllable diffusion models,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Data augmentation for object detection via controllable diffusion models,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.505500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 979b8cdd-792d-4ed1-a794-334c07f94a4f · outbound

This paper cites Exploiting clip self-consistency to automate image augmentation for safety critical scenarios,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Exploiting clip self-consistency to automate image augmentation for safety critical scenarios,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.490859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1f8fea50-b506-4238-b624-b19b8dadd5bf · outbound

This paper cites Op- erationalizing convolutional neural network architectures for prohibited object detection in x-ray imagery,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Op- erationalizing convolutional neural network architectures for prohibited object detection in x-ray imagery,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.475630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation afbfa870-7159-496d-8c37-a62a7c51f1f0 · outbound

This paper cites Generalized cross entropy loss for training deep neural networks with noisy labels,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Generalized cross entropy loss for training deep neural networks with noisy labels,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.461131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5b4df0f6-a4b6-4a03-a6be-0e834ef19d31 · outbound

This paper cites Co-learning: Learning from noisy labels with self-supervision,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Co-learning: Learning from noisy labels with self-supervision,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.438669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6dfdab1b-b9cc-4901-94c8-a6868a1f2361 · outbound

This paper cites Training deep neural-networks using a noise adaptation layer,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Training deep neural-networks using a noise adaptation layer,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.423381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c1f7f0ea-ba5b-4b55-89cc-30e71aa81341 · outbound

This paper cites Making deep neural networks robust to label noise: A loss correction approach,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Making deep neural networks robust to label noise: A loss correction approach,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.410296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 32099b78-1bae-4058-8018-c7d7cef43424 · outbound

This paper cites Part-dependent label noise: Towards instance-dependent label noise,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Part-dependent label noise: Towards instance-dependent label noise,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.396096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 06489f3c-7f8f-46a0-90dd-bb8e9636d758 · outbound

This paper cites Provably end-to-end label-noise learning without anchor points,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Provably end-to-end label-noise learning without anchor points,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.379609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d7ddf932-3f57-4a49-8bbb-9141c29c8ccf · outbound

This paper cites Robust loss functions under label noise for deep neural networks,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Robust loss functions under label noise for deep neural networks,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.366570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ebf0b0f0-8233-4e21-9456-dfec4540d387 · outbound

This paper cites Normalized loss functions for deep learning with noisy labels,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Normalized loss functions for deep learning with noisy labels,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.351999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f7d87395-cd05-4569-80ae-53a7912d2183 · outbound

This paper cites MentorNet: Learning data-driven curriculum for very deep neural networks on corrupted labels,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations MentorNet: Learning data-driven curriculum for very deep neural networks on corrupted labels,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.338298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c67170bc-8848-4039-8a14-2ee0e979e9bf · outbound

This paper cites How does disagreement help generalization against label corruption?.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations How does disagreement help generalization against label corruption?

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.323177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 79e4c6fc-0807-48e5-83d5-03d9dcb8b804 · outbound

This paper cites Combating noisy labels by agreement: A joint training method with co-regularization,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Combating noisy labels by agreement: A joint training method with co-regularization,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.308925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 47d40018-a2bb-482f-b00d-5446e805d875 · outbound

This paper cites Decoupling Representation and Classifier for Long-Tailed Recognition.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Decoupling Representation and Classifier for Long-Tailed Recognition

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-10T22:26:28.876445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51c18a78-380e-42cc-bfc4-52775b23ee22 · outbound

This paper cites PurifyNet: A robust person re-identification model with noisy labels,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations PurifyNet: A robust person re-identification model with noisy labels,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.294842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4fadd584-adb4-45c3-9ba2-4e6634d2cf2a · outbound

This paper cites Collaborative refining for person re-identification with label noise,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Collaborative refining for person re-identification with label noise,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.281499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3099563e-0af5-470a-b7de-6179917aba8f · outbound

This paper cites Structure-aware positional transformer for visible-infrared person re-identification,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Structure-aware positional transformer for visible-infrared person re-identification,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.268698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 759c5887-2cd2-44e0-839d-a887e8524adf · outbound

This paper cites The Good, the Bad and the Ugly: Evaluating Convolutional Neural Networks for Prohibited Item Detection Using Real and Synthetically Composited X-ray Imagery.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations The Good, the Bad and the Ugly: Evaluating Convolutional Neural Networks for Prohibited Item Detection Using Real and Synthetically Composited X-ray Imagery

Reference 51

Resolution: verified exact; local_arxiv, observed 2026-08-10T22:26:29.002844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 489a7902-2be1-4e74-9ec5-c347630e48ea · outbound

This paper cites Rwsc-fusion: Region-wise style-controlled fusion network for the prohibited x-ray 16 security image synthesis,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Rwsc-fusion: Region-wise style-controlled fusion network for the prohibited x-ray 16 security image synthesis,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.254718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ec1bbbc3-7cdc-466e-9c25-fb2cf3da7075 · outbound

This paper cites A logarithmic x-ray imaging model for baggage inspection: Simulation and object detection,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations A logarithmic x-ray imaging model for baggage inspection: Simulation and object detection,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.238885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9c975b4d-1c15-4c5e-a413-884ec5e71fbe · outbound

This paper cites Threat image projection (tip) into x-ray images of cargo containers for training humans and machines,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Threat image projection (tip) into x-ray images of cargo containers for training humans and machines,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.225246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7b1f4700-4c0e-4f0a-b2a0-1c3078381ff0 · outbound

This paper cites CutMix: Reg- ularization strategy to train strong classifiers with localizable features,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations CutMix: Reg- ularization strategy to train strong classifiers with localizable features,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.211373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 530a583f-9bbe-47e0-927c-f9d227a21644 · outbound

This paper cites Saliencymix: A saliency guided data augmentation strategy for better regularization,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Saliencymix: A saliency guided data augmentation strategy for better regularization,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.199364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1cfbf34e-5619-47b0-86fb-1f2509d72dd1 · outbound

This paper cites Attentive cutmix: An enhanced data augmentation approach for deep learning based image classification,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Attentive cutmix: An enhanced data augmentation approach for deep learning based image classification,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.186091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7676c3c5-2ad7-479c-b7eb-08394153718f · outbound

This paper cites Faster R-CNN: Towards real-time object detection with region proposal networks,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Faster R-CNN: Towards real-time object detection with region proposal networks,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.169424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f41d7d06-37ac-468b-86df-f1195887beba · outbound

This paper cites ImageNet classification with deep convolutional neural networks,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations ImageNet classification with deep convolutional neural networks,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.153759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 59762ea9-07c3-45ac-bcea-d11160e90329 · outbound

This paper cites Focal loss for dense object detection,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Focal loss for dense object detection,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.137427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ee1ba136-3958-44da-973d-a1dc95bb563f · outbound

This paper cites Cascade R-CNN: Delving into high quality object detection,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Cascade R-CNN: Delving into high quality object detection,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.122089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d6a897d9-2530-4d58-a369-2f5ff58f9502 · outbound

This paper cites Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection,.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:26:29.106541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b5f58a70-2a15-40c3-a20a-b163442a5016 · outbound

This paper cites MMDetection: Open MMLab Detection Toolbox and Benchmark.

Augmentation Matters: A Mix-Paste Method for X-Ray Prohibited Item Detection under Noisy Annotations MMDetection: Open MMLab Detection Toolbox and Benchmark

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-10T22:26:28.940182Z

Source-reported events for the cited work

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