YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection | Paper Citation Record

Observation e680273a-eb9a-4af6-b8b9-2035517f8423 · outbound

This paper cites Long-Term TalkingFace Generation via Motion-Prior Conditional Diffusion Model.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Long-Term TalkingFace Generation via Motion-Prior Conditional Diffusion Model

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T22:34:32.776804Z

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Unavailable: canonical work link unavailable.

Observation d312cb52-27a0-407c-9ab6-e90f84cce23b · outbound

This paper cites Imagharmony: Controllable image editing with consistent object quantity and layout,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Imagharmony: Controllable image editing with consistent object quantity and layout,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T22:34:32.878617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1df4e27a-d0c0-437e-a1ed-0ca28f242d51 · outbound

This paper cites Rich feature hierarchies for accurate object detection and semantic segmentation,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Rich feature hierarchies for accurate object detection and semantic segmentation,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T22:34:32.956875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22a26a6f-4e5f-4b0d-81c4-d479d63f449c · outbound

This paper cites Fast r-cnn,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Fast r-cnn,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:43.261671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 27b806c9-0ca5-4203-8836-249a6970081e · outbound

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

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Faster r-cnn: Towards real-time object detection with region proposal networks,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:43.084400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 032caaa6-45ca-4b12-92a8-380f16965dcd · outbound

This paper cites Mask r-cnn,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Mask r-cnn,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T22:34:33.203311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6c6663c-d28f-4127-a7a6-219ccd0b577a · outbound

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

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Cascade r-cnn: Delving into high quality object detection,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:42.866019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 213feb41-4564-495e-8850-65a9288ca32e · outbound

This paper cites Region proposal by guided anchoring,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Region proposal by guided anchoring,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:42.686771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 220c4f74-c731-4fd6-bb84-ec209cf1f29d · outbound

This paper cites Cascade rpn: Delving into high-quality region proposal network with adaptive convolution,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Cascade rpn: Delving into high-quality region proposal network with adaptive convolution,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:42.493951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6e2c9ea5-216c-463b-99a5-f2774e08c124 · outbound

This paper cites Ssd: Single shot multibox detector,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Ssd: Single shot multibox detector,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:42.285888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c991006b-e806-4c60-8702-9cd3728ff575 · outbound

This paper cites YOLOv3: An Incremental Improvement.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection YOLOv3: An Incremental Improvement

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T22:34:33.522708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac169ae5-06f4-4690-92cc-13f4fc77a37d · outbound

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

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection YOLOv4: Optimal Speed and Accuracy of Object Detection

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T22:34:33.599085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 474b8bb4-d804-40f5-a018-3c1fff16a85c · outbound

This paper cites Yolov1 to v8: Unveiling each variant–a comprehensive review of yolo,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Yolov1 to v8: Unveiling each variant–a comprehensive review of yolo,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:42.108541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eb88c53d-ffaa-4513-8377-75280d84867d · outbound

This paper cites Metal surface defect detection using SLF-YOLO enhanced YOLOv8 model,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Metal surface defect detection using SLF-YOLO enhanced YOLOv8 model,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:41.887887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5a616715-2133-46f5-88d5-1ca7dc5dbc97 · outbound

This paper cites Aff-net: A strip steel surface defect detec- tion network via adaptive focusing features,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Aff-net: A strip steel surface defect detec- tion network via adaptive focusing features,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:41.636466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d67709f9-26cf-4ca0-8a38-dc23bdd3483f · outbound

This paper cites Multi-scale ship target detection using sar images based on improved yolov5,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Multi-scale ship target detection using sar images based on improved yolov5,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:41.367434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6fde2d7f-49d9-4b96-9de3-c8a626dcc684 · outbound

This paper cites Yolo-lfpd: A lightweight method for strip surface defect detection,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Yolo-lfpd: A lightweight method for strip surface defect detection,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:41.191256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2fbf55c6-c874-4111-a82a-8a07c61f124c · outbound

This paper cites IMAGGarment: Fine-Grained Garment Generation for Controllable Fashion Design.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection IMAGGarment: Fine-Grained Garment Generation for Controllable Fashion Design

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T22:34:33.955681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65c440f7-1835-4c2b-abdb-b73471eb94bb · outbound

This paper cites Imagdressing-v1: Customizable virtual dressing,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Imagdressing-v1: Customizable virtual dressing,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:41.013478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 29dca472-ea31-41dc-9834-dd843a58242b · outbound

This paper cites Imagpose: A unified conditional framework for pose-guided person generation,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Imagpose: A unified conditional framework for pose-guided person generation,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T22:34:34.076519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b0f06b8-6ff1-4a23-9631-5babb5eb4301 · outbound

This paper cites You only look once: Unified, real-time object detection,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection You only look once: Unified, real-time object detection,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T22:34:34.119220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99313f2f-ad09-4227-bd90-1eeab338e47f · outbound

This paper cites an unresolved cited work.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:34:40.820414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fea75711-897d-46ac-86b8-8f987518132f · outbound

This paper cites Yolo-world: Real-time open- vocabulary object detection,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Yolo-world: Real-time open- vocabulary object detection,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:40.577789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e7f5914b-9d0d-48a9-89ea-a8b05ba4168d · outbound

This paper cites QCF-YOLO: A lightweight model of surface defect detection for quick-connect fittings,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection QCF-YOLO: A lightweight model of surface defect detection for quick-connect fittings,

Reference 24

Resolution: verified exact; raw_fallback, observed 2026-08-06T22:34:36.721549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7da1341f-f1f9-4589-8ce5-ba8c2d904c27 · outbound

This paper cites A novel cross frequency-domain interaction learning for aerial oriented object detection,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection A novel cross frequency-domain interaction learning for aerial oriented object detection,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:40.408734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 17bf6ef8-ea4e-4a5e-b5df-c122100bb3a1 · outbound

This paper cites A novel multi-frequency coordinated module for sar ship detection,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection A novel multi-frequency coordinated module for sar ship detection,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:40.229966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3c3fde1d-88d1-46f0-a6b1-b692c5f3fd36 · outbound

This paper cites Attention is all you need,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Attention is all you need,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T22:34:34.489412Z

Source-reported events for the cited work

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Observation fe839587-f2c5-46cc-ab3d-5b35dc48b09e · outbound

This paper cites Squeeze-and-excitation networks,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Squeeze-and-excitation networks,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T22:34:34.551983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80d7d8f8-4989-4921-8892-51ad42969ae4 · outbound

This paper cites Cbam: Convolutional block attention module,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Cbam: Convolutional block attention module,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:39.998772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9adc57c9-fb2f-4d5d-8d27-df81c98ea4ce · outbound

This paper cites Yolo-hmc: An improved method for pcb surface defect detection,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Yolo-hmc: An improved method for pcb surface defect detection,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:39.785249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 62159c57-23d8-4436-96b6-2fe9e3136aa4 · outbound

This paper cites Enhancing aerial object detection with selective frequency interaction network,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Enhancing aerial object detection with selective frequency interaction network,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:39.638454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7e4e632d-eecb-45b8-876e-ec0aa8a54c85 · outbound

This paper cites LR-FPN: Enhancing Remote Sensing Object Detection with Location Refined Feature Pyramid Network.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection LR-FPN: Enhancing Remote Sensing Object Detection with Location Refined Feature Pyramid Network

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T22:34:34.819159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba2d345a-c5e8-4330-92b8-c86aca247198 · outbound

This paper cites dataset., in : https://github.com/lvxiaoming2019/GC10-DET-metallic-surface-defect- datasets.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection dataset., in : https://github.com/lvxiaoming2019/GC10-DET-metallic-surface-defect- datasets

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:39.448898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8c37ceee-6766-4402-b087-8ec0b487ce2b · outbound

This paper cites Weakly supervised learning of a classifier for unusual event detection,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Weakly supervised learning of a classifier for unusual event detection,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:39.250427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4bd9d164-1e3c-4237-8599-4b76a261dbd3 · outbound

This paper cites an unresolved cited work.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Unresolved cited work

Reference 35

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:34:39.038349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation abe1dcf1-fed8-48e9-b5ba-acef6c12a275 · outbound

This paper cites Joining spatial deformable con- volution and a dense feature pyramid for surface defect detection,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Joining spatial deformable con- volution and a dense feature pyramid for surface defect detection,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:38.862937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation dc137ecf-67fe-4d22-a424-e97f5456ec87 · outbound

This paper cites Es-net: Efficient scale-aware network for tiny defect detection,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Es-net: Efficient scale-aware network for tiny defect detection,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:38.623751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fc21f06c-0083-4a08-a4df-d383b4409cc1 · outbound

This paper cites Cspnet: A new backbone that can enhance learning capability of cnn,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Cspnet: A new backbone that can enhance learning capability of cnn,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:38.413945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9018adfe-f1f2-4d21-9b11-0dea78476a88 · outbound

This paper cites Spatial pyramid pooling in deep convolutional net- works for visual recognition,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Spatial pyramid pooling in deep convolutional net- works for visual recognition,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:38.311835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 34d19331-75bc-4337-8e01-f3f665f9b852 · outbound

This paper cites Research on a metal surface defect detection algorithm based on dsl-yolo,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Research on a metal surface defect detection algorithm based on dsl-yolo,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:38.186118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 82de762e-db7b-4ab9-a5dc-8302e8a30720 · outbound

This paper cites Steel surface defect detection based on multi-layer fusion networks,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Steel surface defect detection based on multi-layer fusion networks,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:38.066748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c75f10e2-ed34-427e-949c-b226c965cb64 · outbound

This paper cites Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:37.917692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 30010bc7-65af-41ca-8594-45c592d298ac · outbound

This paper cites Object detection method for grasping robot based on improved yolov5,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Object detection method for grasping robot based on improved yolov5,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:37.747454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 44dec669-b7e5-4245-9b71-9c107d28fef3 · outbound

This paper cites Steel surface defect detection based on mobilevitv2 and yolov8,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Steel surface defect detection based on mobilevitv2 and yolov8,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:37.607142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 895d18ff-a6e1-48d7-9eb3-5acd25cd838c · outbound

This paper cites Msb r-cnn: A multi-stage balanced defect detection network,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Msb r-cnn: A multi-stage balanced defect detection network,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:37.471408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2d24a406-2208-4a05-ab67-7b84553c46e9 · outbound

This paper cites Hic-yolov5: Improved yolov5 for small object detection,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Hic-yolov5: Improved yolov5 for small object detection,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:37.300188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ee1594cd-32c9-4f64-8ba0-24bb207c2421 · outbound

This paper cites Chained cascade network for object detec- tion,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Chained cascade network for object detec- tion,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:37.143324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a656a4f0-5214-4537-bd3a-c183a74b9410 · outbound

This paper cites Yolov9: Learning what you want to learn using programmable gradient information,.

YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection Yolov9: Learning what you want to learn using programmable gradient information,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:34:36.990651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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