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Paper Citation Record · LEDGER

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

As of 10 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2506.21135.

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

pith.paper-citation-record.v1
2506.21135 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:34:36.371474Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

48 of 48 outbound references displayed

  • verified exact1
  • verified fuzzy33
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:34:32.776804Z digest=sha256:2bd313c8e98a0d1547da82fffcf9af35274d6d6b406f59b3e113c8df8569a3b9

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:34:32.878617Z digest=sha256:005244baeb1ad28fce09be0b9e27b79683949fb7860959f241155b88c6c31e54

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:34:32.956875Z digest=sha256:e0a7d5a54fd06ff70c70b8931373a40f9b40a0813d8953834f82dba1c863cfc2

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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:33.057812Z digest=sha256:f96789c769537a0796594cc731a1b1b91332a0f2b050da88534e363fefbe019d

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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:33.133326Z digest=sha256:af4c16c110f99fe495d18c276eeb33828baa7cd5e7b396048407a08daa06ca94

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:34:33.203311Z digest=sha256:2310855f560fc69ad9e0d153a2e4755d2e520d7951878704d550f642635cd043

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:33.282548Z digest=sha256:8674693da03d9e618503e22c8acd4f79ad652fe6b878b1f6b35da77f5e7d4121

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:33.321823Z digest=sha256:aa3ca9b4ae35107857700865d2d0d0fd61ca7b6591033d2640ec1f0890b9804c

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:33.367072Z digest=sha256:c53e7bc77971b8ad934f07cde7f5748710322e932ae659f4b144d5174a35abf8

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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:33.449386Z digest=sha256:d213daecce02c08e9410bf2e52969ca7125b42fdb89f05953f4b2de2a5768d17

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:34:33.522708Z digest=sha256:4947a5874be53b1ba6a4535ad000365161490c16a721cb22bc25f25e6e6f068a

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:34:33.599085Z digest=sha256:87906ec21b594a105403fb7e08a6d154e815fe588436ed0f550383dd986ee687

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:33.643931Z digest=sha256:826778eb5790fafa7f0ca9b15b194569d3decbafce98e606de6c378851dfbe45

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:33.708327Z digest=sha256:107396a700c62af6f088665e590fb00a4aa6cb44831a66f082f946b4caeefd4b

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:33.781625Z digest=sha256:272e7a2783b5beec37d05ff99159a1203093b723a146649e14ded416fbe947da

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:33.852788Z digest=sha256:2152b71101e1af69a12171b0cb991029c1c0eac6794dfa9b836df0f39cd521e4

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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:33.919624Z digest=sha256:021d231a7efc81f91fcebe41f4281d86b4839b3d6310548b9db032461fb19e4f

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:34:33.955681Z digest=sha256:7d8a8faa5e6c49aa4c93c4ef9ceec468b8fb7973d245c50028511b1618cc9308

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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:34.019944Z digest=sha256:84e393f4bfc5bd96ad4a056f35c80ff6ecab73598cc76e5342f29a005689c456

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:34:34.076519Z digest=sha256:f650fd5bc6a5b85078215d13ec3f1664df44c9887537e69ea4ab0097e09abca3

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:34:34.119220Z digest=sha256:7362594b706a074bb72347f99e32ddd052af36092800e841f21a4eaad9b5f62d

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

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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 2026-08-10T06:31:04.303077+00:00.

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:34.239979Z digest=sha256:d8e0b2cc4523fe35366662809d92f849730b07a3544d750ab389ccb849bd875a

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:34.325491Z digest=sha256:2e2af6300a7887e6cc3aabe61cc776defcfc682cee558854186b6245b961e6ee

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:34.368942Z digest=sha256:d81256088167691ea7ab0b0d4c2753c42e0550f750ddbfdf7352b5014ddd22a6

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:34.428480Z digest=sha256:cce6d3de6ccb13f62334898206cac9856873d00c83d93a64443d908fb757ea84

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:34:34.489412Z digest=sha256:19f8fc90bd5fbd55a49ab11ff39f4b070218ba8fd6032f4d81d58528c9be406b

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.

source=pdf_text observed=2026-08-06T22:34:34.551983Z digest=sha256:1a43f33a99a36556acd88b1c7225e7a135c9d26e2919a054046cf0256631072a

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:34.610229Z digest=sha256:2143d0380bd2660bc2410d1062db6d76092c95b35100df450c73cc98fdb5c171

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:34.682990Z digest=sha256:8c73cc5ab8673ec49cfe80e32715847218c5aee88685903bf60611e2ec82d957

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:34.755955Z digest=sha256:4cd3112892b3cae2e3d07f1e5dd1df85024ad128366ac0e5675a4a1bd955c8b2

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.

source=pdf_text observed=2026-08-06T22:34:34.819159Z digest=sha256:37299bc50a8fd1551c97e8d8a27ae27e97a8af2f31d92d894539d7c9c2a8db58

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:34.879874Z digest=sha256:152d35502150969edd89c88d94821001f4d157f6e33a03d2971aa45a532754fc

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:34.885372Z digest=sha256:6000956d52fe2769a5580a51b8d89998916fa6417735c175ce41bfb97b325fce

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:34.958861Z digest=sha256:de9c71669262ce4e41771d64d58d77bc4854adfd3b9bcd3308aaae73ae554477

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:35.157410Z digest=sha256:ddd657ba6815ee1e5360f162c425557b086217912a1815358238e8744f7ed58f

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:35.315237Z digest=sha256:93ce32ea8551458b84c8f3a8acb9a78a39d07873b345bc3e6aba0cc1d4c812aa

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:35.508747Z digest=sha256:525476a973c5ef655f85fadad01a69e24ca193309eced72345b1a9252ea3a0e7

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:35.683881Z digest=sha256:aadf59299b022cdd7303161e0c48de8b00348aedb6afb32fbaaf8cbc4c056841

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:35.747948Z digest=sha256:488796872285c65c61dd5d0dea6294df153dafa3dce6232cd78c06e9ee98e05a

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:35.786003Z digest=sha256:37721d66d008488e399963c09616591b5985bf272a8e7a8cc6401886ba4a6a4f

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:35.868198Z digest=sha256:0f69fe27e0b7d43a931afc074f3ddb4e2e62bc22c6116aab9313d0e59eb1ad10

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:35.977224Z digest=sha256:1e62836f2b5e38213f7e1b4b040a421c4aa1c61a10d26d3befb476d60c1d7fc5

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:36.126837Z digest=sha256:4ad4fbd538b303b2dfd6e2796eef21adbdece3234e711f519af9bb8fe8c35166

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:36.182930Z digest=sha256:b7f169c8ba225674ffc09230823882fd9ad80fda8825738ef5fe4df7711b8034

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:36.286858Z digest=sha256:e4387f9d7e110759966a1369313175ac1b9ebb495d29de9c8a4eae39b15b2125

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:36.339187Z digest=sha256:3778f7393fefe62b1886aac59509cf21ce9b0892410d32a4d8e038fcd0eb89b4

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T22:34:36.371474Z digest=sha256:3a2e3f2b43de610058d84d57e95bf0237e9b1e00709040a721853a686316a659

Pith citing papers

No inbound Pith citation observations are available.