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Paper Citation Record · LEDGER

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection

As of 15 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2412.03969.

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

pith.paper-citation-record.v1
2412.03969 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:58:08.483491Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

50 of 50 outbound references displayed

  • verified exact0
  • verified fuzzy42
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 10222a4b-ae74-4505-aee4-6560d4766213 · outbound

This paper cites Process manufacturing intelligence empowered by industrial JOURNAL OF LATEX CLASS FILES, VOL. 18, NO. 9, SEPTEMBER 2020 12 metaverse: A survey,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Process manufacturing intelligence empowered by industrial JOURNAL OF LATEX CLASS FILES, VOL. 18, NO. 9, SEPTEMBER 2020 12 metaverse: A survey,

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-11T21:58:09.228566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.255668Z digest=sha256:0a574cde4856e85da8f1ec1e11fec03d79b578e6407a537712f6496d3f255ce5

Observation e7c97810-2eeb-4848-9762-7d805adbd74c · outbound

This paper cites Moninet with concurrent analytics of temporal and spatial information for fault detection in industrial processes,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Moninet with concurrent analytics of temporal and spatial information for fault detection in industrial processes,

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-11T21:58:09.213969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.261304Z digest=sha256:8d2241cfc2267bd00b30242d00adc8d6b16d01cd7984ba877c6c02a31b442dd7

Observation 6b0d8874-5cd8-4357-b9cf-0234cba8ec62 · outbound

This paper cites Context-aware block net for small object detection,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Context-aware block net for small object detection,

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-11T21:58:09.198479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.266109Z digest=sha256:c8e2ea43e562d5a59f827c74cb1faad8606b6722eb3d93f83f12260b59283635

Observation 5c3a3630-77f0-4179-b885-add1955840e3 · outbound

This paper cites Enhancing geometric factors in model learning and inference for object detection and instance segmentation,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Enhancing geometric factors in model learning and inference for object detection and instance segmentation,

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-11T21:58:09.184161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.271004Z digest=sha256:56ae3ca6576fdd40fb0eac30bd05610f136b6c826b2196058498fa4a22a72b12

Observation a8f8e8da-a19c-4eae-a720-75dbce31dab9 · outbound

This paper cites Taanet: A task-aware attention network for weak surface defect detection,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Taanet: A task-aware attention network for weak surface defect detection,

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-11T21:58:09.169283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.275995Z digest=sha256:489e826699c40aa1cc271e6a9d293d897ef870fc4bcd25ddfa27541f098291bf

Observation ea516408-b24b-4064-9e09-5328d820de83 · outbound

This paper cites Clip-fsac: Boosting clip for few-shot anomaly classification with synthetic anomalies,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Clip-fsac: Boosting clip for few-shot anomaly classification with synthetic anomalies,

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-11T21:58:09.154526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.281000Z digest=sha256:6d2eb965307cc0ebc432ab14fa2d7654981dd9184a61abb41a0495cc3953c8eb

Observation 0c909ac2-1865-49f9-8d96-d58296188928 · outbound

This paper cites A reconstruction-based feature adaptation for anomaly detection with self-supervised multi-scale aggregation,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection A reconstruction-based feature adaptation for anomaly detection with self-supervised multi-scale aggregation,

Reference 7

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raw_fallback, observed 2026-08-11T21:58:09.139832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.286325Z digest=sha256:385cb24848f99d32d58c9e56f2be454253b5f208fec31b8335116dbe6146e91b

Observation 1a9cdd1a-cfbf-4bd5-b7b9-a840d7d16331 · outbound

This paper cites Ultralytics YOLOv8,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Ultralytics YOLOv8,

Reference 8

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unresolved
no resolver link, observed 2026-08-11T21:58:08.290722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:58:08.290722Z digest=sha256:53109c7f556d72c65ea2192180a16d7c32f01169c8036e0e8104f3e3329fc933

Observation 31db0ff7-10f1-4fda-939d-0fa00e84c367 · outbound

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

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Faster r-cnn: Towards real-time object detection with region proposal networks,

Reference 9

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unresolved
no resolver link, observed 2026-08-11T21:58:08.295113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:58:08.295113Z digest=sha256:039bfc894f2e5654f4b57e6bace5be4b050eec686d4727501c946809d214fbe6

Observation 5251fbe8-0650-4dff-871d-c389d1dcef0d · outbound

This paper cites Detrs beat yolos on real-time object detection,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Detrs beat yolos on real-time object detection,

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-11T21:58:09.106156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.299479Z digest=sha256:1d2f1d6bea45914f5ce8acefa8089bf686d90a051bde39345c3e511613c4108f

Observation b8a72868-814f-45cc-93a4-f5c70dfc3cc1 · outbound

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

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Yolo-hmc: An improved method for pcb surface defect detection,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:09.092451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.303902Z digest=sha256:f10a7a6d114f34274ba632dd014a21ae05667113594e979165e4b0bbfc7c73a9

Observation 2b00e5a7-81cd-446e-b105-702340bd7a78 · outbound

This paper cites Adin-detr: Adapting detection transformer for end-to-end real-time power line insulator defect detection,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Adin-detr: Adapting detection transformer for end-to-end real-time power line insulator defect detection,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:09.077776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.308435Z digest=sha256:080c1dccfb43deda587c17e1861646b45fa0f87759daa4685d6d12396b00802d

Observation b23ee4be-cb8a-45e5-9876-a345c077fc44 · outbound

This paper cites An optical lens defect detection method for micro vision based on wgso-yolo,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection An optical lens defect detection method for micro vision based on wgso-yolo,

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-11T21:58:09.064133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.312795Z digest=sha256:895e30b4f08a920dc3b70d899db5fffbd371031f189456c58056c07b1a4a4731

Observation 6bdeeef8-621e-4942-9be1-f577690306be · outbound

This paper cites Carafe: Content-aware reassembly of features,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Carafe: Content-aware reassembly of features,

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-11T21:58:09.050127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.317292Z digest=sha256:285a5fa620f448fbb5a4a383729af8162077a8c25f2ad3e86834677ff445ada8

Observation a76c5ad7-8a47-47bc-bdf5-75055fc4e6d9 · outbound

This paper cites An efficient anchor-free defect detector with dynamic receptive field and task alignment,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection An efficient anchor-free defect detector with dynamic receptive field and task alignment,

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-11T21:58:09.036215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.321824Z digest=sha256:d02e5c8ea9a097b881b31740cbc907e96ffeb3a8e002286a9b660361382f3899

Observation f4d43317-c9f7-410e-9f2b-c4a134364e95 · outbound

This paper cites Mci-gla plug-in suitable for yolo series models for transmission line insulator defect detection,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Mci-gla plug-in suitable for yolo series models for transmission line insulator defect detection,

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-11T21:58:09.022094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.326290Z digest=sha256:c941f5207e7b3b48b1e9d921c7fe29725561ce22bd4f3a06ce1736c89f632067

Observation cffdafd7-4550-4f65-9011-23569840506e · outbound

This paper cites Hripcb: a challenging dataset for pcb defects detection and classification,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Hripcb: a challenging dataset for pcb defects detection and classification,

Reference 17

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verified fuzzy
raw_fallback, observed 2026-08-11T21:58:09.008049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.330733Z digest=sha256:8a0627ba42d9ba77889c3ec5ec950fcedd245b72bba93166628f35771b6694fe

Observation 366a8413-a541-4f91-b7ea-56d29db002a5 · outbound

This paper cites An end-to-end steel surface defect detection approach via fusing multiple hierarchical features,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection An end-to-end steel surface defect detection approach via fusing multiple hierarchical features,

Reference 18

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raw_fallback, observed 2026-08-11T21:58:08.993500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.335239Z digest=sha256:b411529b097e0143b9c53b886f4058ac38bdd30de73107917155fc6b7611d226

Observation 69eb90f3-df36-4ab4-99d2-05fd7a4e5185 · outbound

This paper cites Multilevel fine- grained features-based general framework for object detection,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Multilevel fine- grained features-based general framework for object detection,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.979338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.339557Z digest=sha256:545fefe1fb2cbe9462d849fd3fb1b8e31753de5155f0db96a123d28d969140f7

Observation 8d25f3e6-5c2f-4efe-9291-27fe8b99db73 · outbound

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

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Joining spatial deformable convolution and a dense feature pyramid for surface defect detection,

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.964640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.343877Z digest=sha256:87e7d8be0f6c2ef8f64aac8a61ea4fef2016a1691a9d6eb5c67ebd6f30454394

Observation 1ee1eedb-f42c-4b5e-beec-89da35e5561f · outbound

This paper cites Pcb-yolo: An improved detection algorithm of pcb surface defects based on yolov5,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Pcb-yolo: An improved detection algorithm of pcb surface defects based on yolov5,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.950413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.348357Z digest=sha256:36a2434d1c73a1d7a92ce82ec7a2242b00791b6f7dadcca2c5a963a019bc11e3

Observation fa5fd27f-2330-4e21-9483-7b9fafb8d0e2 · outbound

This paper cites Canet: Contextual information and spatial attention based network for detecting small defects in manufacturing industry,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Canet: Contextual information and spatial attention based network for detecting small defects in manufacturing industry,

Reference 22

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verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.937298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.352887Z digest=sha256:4b8a5f0e4e5b6db2bb42245949715bf36c6c2cbbf3a2c677c3b66254e68f4486

Observation 55411ebb-f25a-4c9b-a7d7-2c0e93c47635 · outbound

This paper cites Hypergraph neural networks,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Hypergraph neural networks,

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.923160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.357374Z digest=sha256:d67c58f44f80402234751d547aaf9ca8de9cb9244d5b8813b67eb1063ead5f85

Observation a82559c6-b65e-4007-8727-265c8d87c384 · outbound

This paper cites HGNN+: General hypergraph neural networks,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection HGNN+: General hypergraph neural networks,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.909113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.361709Z digest=sha256:5401ef6d29890d26f4d718db3af701233b0bf0a48b92e561247712bce730d47b

Observation 85cbef8e-cd58-4359-8972-6387355ef5d5 · outbound

This paper cites Lbsn2vec++: Het- erogeneous hypergraph embedding for location-based social networks,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Lbsn2vec++: Het- erogeneous hypergraph embedding for location-based social networks,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.895053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.365899Z digest=sha256:7eae5617ec4e05812f9d6d51970589a3d74acc8999ae9eead0fd5b0cd80f4676

Observation cc6722a1-feb4-4f86-bec3-ef31647d439f · outbound

This paper cites Hypergraph factorization for multi-tissue gene expression imputation,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Hypergraph factorization for multi-tissue gene expression imputation,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.881271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.370404Z digest=sha256:6a4ca7af526f6895d46f60b9b8156c2fe45e6f6a10834f7e7ccd7f68ac9ca0ee

Observation a11b531f-a8f0-4483-8ef7-44049403d103 · outbound

This paper cites Multi-hypergraph learning- based brain functional connectivity analysis in fmri data,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Multi-hypergraph learning- based brain functional connectivity analysis in fmri data,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.867386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.374750Z digest=sha256:be65092249aeb700f886650321c901737ee2a031e3194a339d869c6fb12840c3

Observation 25b8ed64-2b5e-41b6-8574-3ba790f233d6 · outbound

This paper cites Hyper-YOLO: When Visual Object Detection Meets Hypergraph Computation.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Hyper-YOLO: When Visual Object Detection Meets Hypergraph Computation

Reference 28

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unresolved
no resolver link, observed 2026-08-11T21:58:08.380060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:58:08.380060Z digest=sha256:233d04948df026d8cebdd2262c1264131c925f8a9a388a0de8aca69333743f41

Observation c9e8bb8b-5d21-4fa9-8bd0-70210928de26 · outbound

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

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection You only look once: Unified, real-time object detection,

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.852895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.384909Z digest=sha256:26d7d3928fc14710f05978390eebd6b16cc019ed15c577f983a81c8299f7539b

Observation 9de2864c-eacb-4121-82e4-d4def8d99796 · outbound

This paper cites Yolo9000: Better, faster, stronger,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Yolo9000: Better, faster, stronger,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.838590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.389168Z digest=sha256:4d33712127a98733ae925e03f09ace8cc5b164f54caaf5c41b93d657b8515c19

Observation 16f037a8-b133-4fb0-9eab-49fbc7d9c40b · outbound

This paper cites YOLOX: Exceeding YOLO Series in 2021.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection YOLOX: Exceeding YOLO Series in 2021

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-11T21:58:08.393436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:58:08.393436Z digest=sha256:4441bd522aca29a7e0206622b504006c3c2b86cae1a11eb9824a394a235ba6f0

Observation 3e88a906-3e45-4ea5-82dd-89e11ceb337a · outbound

This paper cites YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-11T21:58:08.398049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:58:08.398049Z digest=sha256:91eb2cd3640cfb6e05f58fcd5138848420e95b9e78c1f37b8a40fbf54f91e37b

Observation 05f2d923-6aad-4fb1-9eca-af4f6ff4772d · outbound

This paper cites Repvgg: Making vgg-style convnets great again,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Repvgg: Making vgg-style convnets great again,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.825070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.402969Z digest=sha256:ae3dc16e2b6b494780a0d140e4e7944544c879c4d01f99807d3b519188db2f26

Observation 38cf8490-bceb-4218-b70e-0bf00d83d993 · outbound

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

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Tood: Task- aligned one-stage object detection,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.810386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.407218Z digest=sha256:099db957643bcb77aec31d9a54726a3524ef35e72e52227cd3656f660e7e4110

Observation 35b70f23-ed36-475f-a15d-d2e8f36c8ba2 · outbound

This paper cites YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-11T21:58:08.411574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:58:08.411574Z digest=sha256:d70834f11a021f26e55a2d6b231ce3410f2bbc396f08548dc70fb82533b73fc7

Observation 99fcf800-20f7-40e1-b8db-a6980dcd417b · outbound

This paper cites YOLOv10: Real-Time End-to-End Object Detection.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection YOLOv10: Real-Time End-to-End Object Detection

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-11T21:58:08.416576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:58:08.416576Z digest=sha256:72e4b8bc054e92a57e86755939f13e10bfd7b3e7dd5ec1029adcdc309f94a1d2

Observation 306bf583-b17d-4a75-9b6a-de849ece3e94 · outbound

This paper cites Ultralytics YOLOv11,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Ultralytics YOLOv11,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.796377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.421637Z digest=sha256:297953bca3f8cfe257d905ca018b6b10feefeab56c0d7b6e72c06546f0064134

Observation eb7d51ff-5f87-4361-abf8-1008ebeaf48e · outbound

This paper cites Real-time single image and video super- resolution using an efficient sub-pixel convolutional neural network,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Real-time single image and video super- resolution using an efficient sub-pixel convolutional neural network,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.780974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.426032Z digest=sha256:32959474b16b6bc41db76ad37762880458ed8561ebb8d2a00bb4b9a0f39896ee

Observation 928dd12b-b885-481b-b7dd-2a4979990ed7 · outbound

This paper cites YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-11T21:58:08.430773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:58:08.430773Z digest=sha256:5e058ff7deda79dce4142de43dccdd831ca52e98fe19d87cea1571839641d403

Observation 7ceaba4c-eea2-4bac-a346-273e0fd2f0f1 · outbound

This paper cites Detectors: Detecting objects with recursive feature pyramid and switchable atrous convolution,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Detectors: Detecting objects with recursive feature pyramid and switchable atrous convolution,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.766510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.436381Z digest=sha256:17937adb51393b4d949b48335f62dc9738b002b0ad7425a15a7d6fe1b47ce3d2

Observation c129f9f3-7e11-4021-acbb-d29b8a0f2198 · outbound

This paper cites Automatic detection and counting system for pavement cracks based on pcgan and yolo-mf,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Automatic detection and counting system for pavement cracks based on pcgan and yolo-mf,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.751766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.442212Z digest=sha256:254a11da0d688a3b111ed09cb020564bb57713db42b6d9c5227aaca14d3f364e

Observation 85a46d5b-456c-49b1-9a68-73aba9fe198a · outbound

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

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Es-net: Efficient scale- aware network for tiny defect detection,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.736657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.447060Z digest=sha256:94fd08c7af63fbe105d2b2153b7e96ea163cf304194039376d8cf004c7e91d3f

Observation 9212e5d4-404b-4024-a613-e79a49190e7f · outbound

This paper cites Deformable yolox: Detection and rust warning method of transmission line connection fittings based on image processing technology,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Deformable yolox: Detection and rust warning method of transmission line connection fittings based on image processing technology,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.721998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.451571Z digest=sha256:fac370a3a04001445d4df7a95764f173f6e741e66b09f00a359a6438410c03d1

Observation 14bb40ec-85fc-46d3-b11d-d54915c498d9 · outbound

This paper cites An anchor-free defect detector for complex background based on pixelwise adaptive multiscale feature fusion,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection An anchor-free defect detector for complex background based on pixelwise adaptive multiscale feature fusion,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.706684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.456642Z digest=sha256:29fa403e3da8baebacf1339b04bb4d51e6f81be2adab36f1ae971e74ca11f90e

Observation 7d2f288f-7963-455f-9fd2-ee76964fff18 · outbound

This paper cites Attention network for rail surface defect detection via consistency of intersection-over-union(iou)- guided center-point estimation,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Attention network for rail surface defect detection via consistency of intersection-over-union(iou)- guided center-point estimation,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.691341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.461189Z digest=sha256:f3b3ba8fdfd18f4f572c8d4dc3013f294eae9f2d5d0bd660bf2e4f58a36a8839

Observation f2d61f8b-80c0-40f4-bff0-4200681d6eae · outbound

This paper cites Visual fault detection of multiscale key components in freight trains,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Visual fault detection of multiscale key components in freight trains,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.674359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.465727Z digest=sha256:eb0e028a1fdc20dd5fcd993cc2de734dfb06b356d7b5ca5195eeff5022f4398c

Observation b700bf9c-50b1-41e1-b759-c57565cc3fca · outbound

This paper cites Cascade r-cnn: High quality object detection and instance segmentation,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Cascade r-cnn: High quality object detection and instance segmentation,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.659063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.470131Z digest=sha256:19efb19ec06c68e696aa0519a82c427e696b385ae451bcf772fbbc3efe3177a9

Observation e2bc3acb-2122-455d-b06c-9f36afb8004c · outbound

This paper cites Libra r-cnn: Towards balanced learning for object detection,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Libra r-cnn: Towards balanced learning for object detection,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.643914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.474566Z digest=sha256:4c341f36cc2c4928959604e8c8df3fb2e3286b4847f53639ca40f545bc9a325c

Observation 0bae6114-ba1d-423f-9051-607a434f3da6 · outbound

This paper cites Focal loss for dense object detection,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Focal loss for dense object detection,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.628859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.479102Z digest=sha256:7e477e47ced3d979c8816f40654215e0d101bba76aeedfa52cb717f6181278f2

Observation 1afbb31b-929e-40fb-a454-2760f19b1d17 · outbound

This paper cites Fcos: Fully convolutional one- stage object detection,.

HyperDefect-YOLO: Enhance YOLO with HyperGraph Computation for Industrial Defect Detection Fcos: Fully convolutional one- stage object detection,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T21:58:08.612730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T21:58:08.483491Z digest=sha256:8cbb596d27140c6d342b88a6fdb62fcc154cd4993147a3a677ff7fd5f03ceab8

Pith citing papers

No inbound Pith citation observations are available.