Paper Citation Record · LEDGER

What is YOLOv6? A Deep Insight into the Object Detection Model

As of 14 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 2 inbound Pith citation observations for arXiv:2412.13006.

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

pith.paper-citation-record.v1
2412.13006 v1

Coverage vector

measured 66 of 66 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:34:55.398241Z

measured 68 of 68 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:15:57.417539Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T23:20:54.304147Z

Reference resolution

66 of 66 outbound references displayed

verified exact1
verified fuzzy10
unresolved55
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 847db1a5-d0a7-482e-9b09-e6a42df42d35 · outbound

This paper cites A layer-wise surface deformation defect detection by convolutional neural networks in laser powder-bed fusion images.

What is YOLOv6? A Deep Insight into the Object Detection Model A layer-wise surface deformation defect detection by convolutional neural networks in laser powder-bed fusion images

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.086071Z

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Observation f778e034-a717-48f4-ad8a-6618282641ff · outbound

This paper cites Custom lightweight convolutional neural network architecture for automated detection of damaged pallet racking in warehousing & distribution centers.

What is YOLOv6? A Deep Insight into the Object Detection Model Custom lightweight convolutional neural network architecture for automated detection of damaged pallet racking in warehousing & distribution centers

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.091598Z

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Observation 46c2f52f-d3c8-4c6d-9b64-a898a03b9274 · outbound

This paper cites Lightweight convolutional network for automated photovoltaic defect detection.

What is YOLOv6? A Deep Insight into the Object Detection Model Lightweight convolutional network for automated photovoltaic defect detection

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.096553Z

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Observation f0a57a6b-f4a2-4991-9e90-8767131b2d2c · outbound

This paper cites Comparative study of computational time that hog-based features used for vehicle detection.

What is YOLOv6? A Deep Insight into the Object Detection Model Comparative study of computational time that hog-based features used for vehicle detection

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.101467Z

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Observation b89ed80d-f91d-48a2-bfea-2ae946bf3b72 · outbound

This paper cites On combining classifiers.

What is YOLOv6? A Deep Insight into the Object Detection Model On combining classifiers

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.106904Z

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Observation 5dd67d4c-6a6a-4616-b755-053a6302779b · outbound

This paper cites Action recognition by dense trajectories.

What is YOLOv6? A Deep Insight into the Object Detection Model Action recognition by dense trajectories

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.111956Z

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Observation 5968e370-601b-4141-a50d-21488acc31c7 · outbound

This paper cites A database for fine grained activity detection of cooking activities.

What is YOLOv6? A Deep Insight into the Object Detection Model A database for fine grained activity detection of cooking activities

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.117544Z

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Observation 449dd715-dcd7-46ac-b375-8877f2109c9d · outbound

This paper cites Feature mapping for rice leaf defect detection based on a custom convolutional architecture.

What is YOLOv6? A Deep Insight into the Object Detection Model Feature mapping for rice leaf defect detection based on a custom convolutional architecture

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.122334Z

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Observation 82145f8e-a2d0-4eea-9422-52a5adab4a45 · outbound

This paper cites Gun and knife detection based on faster r-cnn for video surveillance.

What is YOLOv6? A Deep Insight into the Object Detection Model Gun and knife detection based on faster r-cnn for video surveillance

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.126959Z

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Observation 2827816c-1fb8-4821-832a-bb34c143d88a · outbound

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

What is YOLOv6? A Deep Insight into the Object Detection Model Rich feature hierarchies for accurate object detection and semantic segmentation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.131148Z

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Observation f8de7ea0-a347-423d-83b9-b709dd5dc7b3 · outbound

This paper cites Stable and compact design of memristive googlenet neural network.

What is YOLOv6? A Deep Insight into the Object Detection Model Stable and compact design of memristive googlenet neural network

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.135318Z

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Observation 5e1ef751-a050-48b7-b504-f2ba2c47bff2 · outbound

This paper cites Brain tumor detection using mask r-cnn.

What is YOLOv6? A Deep Insight into the Object Detection Model Brain tumor detection using mask r-cnn

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.139589Z

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Observation 42263a91-2a22-423e-935c-b916c3c80b87 · outbound

This paper cites Imagenet classification with deep convolutional neural networks.

What is YOLOv6? A Deep Insight into the Object Detection Model Imagenet classification with deep convolutional neural networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.143914Z

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Observation 8bce8bbc-0336-40ca-9cc3-7bb22bed5a27 · outbound

This paper cites Deep residual learning for image recognition.

What is YOLOv6? A Deep Insight into the Object Detection Model Deep residual learning for image recognition

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.147980Z

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Observation 9207d15b-ed17-4546-b440-fb5ad17f7b63 · outbound

This paper cites Pedestrian detection based on faster r-cnn.

What is YOLOv6? A Deep Insight into the Object Detection Model Pedestrian detection based on faster r-cnn

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.151750Z

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Observation 4cc82fab-50cc-4692-8d4a-1b45e1da5ba8 · outbound

This paper cites Classification of picture art style based on vggnet.

What is YOLOv6? A Deep Insight into the Object Detection Model Classification of picture art style based on vggnet

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.155761Z

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Observation 225a58d4-e300-47c4-81e8-ce630ad62799 · outbound

This paper cites Yolo-v5 variant selection algorithm coupled with representative augmentations for modelling production-based variance in automated lightweight pallet racking inspection.

What is YOLOv6? A Deep Insight into the Object Detection Model Yolo-v5 variant selection algorithm coupled with representative augmentations for modelling production-based variance in automated lightweight pallet racking inspection

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:34:56.054357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 57549c85-ed50-45b9-883a-cba73ab56462 · outbound

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

What is YOLOv6? A Deep Insight into the Object Detection Model You only look once: Unified, real-time object detection

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.164272Z

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Observation 7faa2273-3b06-4010-895b-0fb7cfbadaba · outbound

This paper cites A gradient guided architecture coupled with filter fused representations for micro-crack detection in photovoltaic cell surfaces.

What is YOLOv6? A Deep Insight into the Object Detection Model A gradient guided architecture coupled with filter fused representations for micro-crack detection in photovoltaic cell surfaces

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.168658Z

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Observation a38a7c54-a8c9-4c33-822a-8a38d0398d60 · outbound

This paper cites Yolo9000: better, faster, stronger.

What is YOLOv6? A Deep Insight into the Object Detection Model Yolo9000: better, faster, stronger

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.172878Z

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Observation 6ce6e555-b723-41aa-8bcf-704fea85c052 · outbound

This paper cites YOLOv3: An Incremental Improvement.

What is YOLOv6? A Deep Insight into the Object Detection Model YOLOv3: An Incremental Improvement

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.177547Z

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Observation 22157088-b1ba-44c6-a966-cc0a09e3a96e · outbound

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

What is YOLOv6? A Deep Insight into the Object Detection Model YOLOv4: Optimal Speed and Accuracy of Object Detection

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.182693Z

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Observation 063acde1-7b0c-4286-b18c-cc52f133aed5 · outbound

This paper cites Comprehensive guide to ultralytics yolov5, 2023.

What is YOLOv6? A Deep Insight into the Object Detection Model Comprehensive guide to ultralytics yolov5, 2023

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.187794Z

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Observation 26f64788-2e41-43a4-ae37-fe00424a99d2 · outbound

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

What is YOLOv6? A Deep Insight into the Object Detection Model Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.197555Z

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Observation 3e5cd7c7-b8fe-4dcb-8dc6-c2630e1a6f01 · outbound

This paper cites Yolo: A brief history, 2023.

What is YOLOv6? A Deep Insight into the Object Detection Model Yolo: A brief history, 2023

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.202415Z

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Observation de8d6cf0-b1bb-4d60-b657-7d219e8ea2c6 · outbound

This paper cites Isolated bangla handwritten character recognition with convolutional neural network.

What is YOLOv6? A Deep Insight into the Object Detection Model Isolated bangla handwritten character recognition with convolutional neural network

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.206985Z

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Observation 198f5bcb-a661-4502-b33a-8e93be11738f · outbound

This paper cites Yolo object detection explained, 2024.

What is YOLOv6? A Deep Insight into the Object Detection Model Yolo object detection explained, 2024

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:34:55.966716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation dc2eddfe-a5a7-4fe7-8d7b-4ef9e2bd1869 · outbound

This paper cites Using deep convolutional neural network architectures for object classification and detection within x-ray baggage security imagery.

What is YOLOv6? A Deep Insight into the Object Detection Model Using deep convolutional neural network architectures for object classification and detection within x-ray baggage security imagery

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.216624Z

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Observation ab1973e0-b061-4695-a2a3-984ffc6a097d · outbound

This paper cites A frame-work assisting the visually impaired people: common object detection and pose estimation in surrounding environment.

What is YOLOv6? A Deep Insight into the Object Detection Model A frame-work assisting the visually impaired people: common object detection and pose estimation in surrounding environment

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.221381Z

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Observation dc9aea4c-4997-4913-95be-a093b5be6532 · outbound

This paper cites An evaluation of yolo-based algorithms for hand detection in the kitchen.

What is YOLOv6? A Deep Insight into the Object Detection Model An evaluation of yolo-based algorithms for hand detection in the kitchen

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.225999Z

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Observation f50aa8e5-7cca-4aa0-a89d-4f2a64f8ddad · outbound

This paper cites Improved yolov4 algorithm for safety management of on-site power system work.

What is YOLOv6? A Deep Insight into the Object Detection Model Improved yolov4 algorithm for safety management of on-site power system work

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.230782Z

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Observation f50a82a9-217f-4eaa-acdc-1ac52baca3d7 · outbound

This paper cites You only learn one representation: Unified network for multiple tasks.

What is YOLOv6? A Deep Insight into the Object Detection Model You only learn one representation: Unified network for multiple tasks

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.235508Z

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Observation 70b19032-a899-4899-8195-c37ece4e4ac0 · outbound

This paper cites Complete and accurate holly fruits counting using yolox object detection.

What is YOLOv6? A Deep Insight into the Object Detection Model Complete and accurate holly fruits counting using yolox object detection

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.244811Z

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Observation 03672c1c-9327-476a-88dd-bbbee2f79a35 · outbound

This paper cites Real-time multiple object tracking for safe cooking activities.

What is YOLOv6? A Deep Insight into the Object Detection Model Real-time multiple object tracking for safe cooking activities

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.249365Z

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Observation 01c36c40-009b-47ae-8dba-4a373e31ef82 · outbound

This paper cites Augmented reality based interactive cooking guide.

What is YOLOv6? A Deep Insight into the Object Detection Model Augmented reality based interactive cooking guide

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.254274Z

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Observation 21173d20-0cb8-49b9-8c06-3f2946ace69c · outbound

This paper cites A Comparative Analysis of YOLOv5, YOLOv8, and YOLOv10 in Kitchen Safety.

What is YOLOv6? A Deep Insight into the Object Detection Model A Comparative Analysis of YOLOv5, YOLOv8, and YOLOv10 in Kitchen Safety

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.258668Z

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Observation 381d2c54-ebd5-411b-bd92-5317f278015e · outbound

This paper cites Comparing YOLOv5 Variants for Vehicle Detection: A Performance Analysis.

What is YOLOv6? A Deep Insight into the Object Detection Model Comparing YOLOv5 Variants for Vehicle Detection: A Performance Analysis

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.263518Z

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Observation d8b8a2f3-8ca8-4102-852c-039b698211a0 · outbound

This paper cites A yolov6-based improved fire detection approach for smart city environments.

What is YOLOv6? A Deep Insight into the Object Detection Model A yolov6-based improved fire detection approach for smart city environments

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.268784Z

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Observation c11c15a4-ce68-42de-a4f0-c8ebd9399f84 · outbound

This paper cites Detection of guns and knives images based on yolo v7.

What is YOLOv6? A Deep Insight into the Object Detection Model Detection of guns and knives images based on yolo v7

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.273405Z

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Observation 093d1a2d-6364-4041-9b52-b63b4d56cff0 · outbound

This paper cites Real time object detection with data variation.

What is YOLOv6? A Deep Insight into the Object Detection Model Real time object detection with data variation

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:34:55.851650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 368ea363-2152-4e96-9f60-e1c402995030 · outbound

This paper cites Comparative analysis of yolov8 and yolov10 in vehicle detection: Performance metrics and model efficacy.Vehicles, 6(3):1364– 1382, 2024.

What is YOLOv6? A Deep Insight into the Object Detection Model Comparative analysis of yolov8 and yolov10 in vehicle detection: Performance metrics and model efficacy.Vehicles, 6(3):1364– 1382, 2024

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.282931Z

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Observation 8dbf82a7-f6ea-4a50-946f-51bfacaa8833 · outbound

This paper cites A comprehensive review of yolo architectures in computer vision: From yolov1 to yolov8 and yolo-nas.

What is YOLOv6? A Deep Insight into the Object Detection Model A comprehensive review of yolo architectures in computer vision: From yolov1 to yolov8 and yolo-nas

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.287615Z

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Observation e8abacaf-2e79-48ae-8442-76e401b5e27b · outbound

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

What is YOLOv6? A Deep Insight into the Object Detection Model Yolov9: Learning what you want to learn using programmable gradient information

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.292576Z

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Observation 7ac17f75-c017-42c4-a6f2-9f408de53f9b · outbound

This paper cites YOLOv1 to YOLOv10: A comprehensive review of YOLO variants and their application in the agricultural domain.

What is YOLOv6? A Deep Insight into the Object Detection Model YOLOv1 to YOLOv10: A comprehensive review of YOLO variants and their application in the agricultural domain

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.297243Z

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Observation a4956732-9e30-4239-8f81-e847cf1d9ea7 · outbound

This paper cites Nikhileswara Rao.

What is YOLOv6? A Deep Insight into the Object Detection Model Nikhileswara Rao

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.301887Z

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Observation 5dece9e4-f277-4019-ac0d-66b0789481ab · outbound

This paper cites YOLOv6 v3.0: A Full-Scale Reloading.

What is YOLOv6? A Deep Insight into the Object Detection Model YOLOv6 v3.0: A Full-Scale Reloading

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.310461Z

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Observation cf2b3693-3b43-421b-9874-8b10d46adeff · outbound

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

What is YOLOv6? A Deep Insight into the Object Detection Model YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.315283Z

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Observation 24165587-3acf-49fa-856a-85dcbdf439f6 · outbound

This paper cites Rethinking the inception architecture for computer vision.

What is YOLOv6? A Deep Insight into the Object Detection Model Rethinking the inception architecture for computer vision

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.319352Z

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Observation a2a6ed04-89dc-4f29-bb4f-02bf84bbd75c · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

What is YOLOv6? A Deep Insight into the Object Detection Model Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.323461Z

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Observation 3892625f-a23e-4f81-94be-7d2f36c6c2db · outbound

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

What is YOLOv6? A Deep Insight into the Object Detection Model Repvgg: Making vgg-style convnets great again

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.328172Z

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Observation ec101ae2-c1dd-4ce1-9a32-90b45496aba8 · outbound

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

What is YOLOv6? A Deep Insight into the Object Detection Model Cspnet: A new backbone that can enhance learning capability of cnn

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.332267Z

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Observation f9e361ea-baa1-487a-a20d-eca586210667 · outbound

This paper cites Path aggregation network for instance segmentation.

What is YOLOv6? A Deep Insight into the Object Detection Model Path aggregation network for instance segmentation

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.336876Z

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Observation 769dcbb8-1f8f-4806-8bc2-5baa1d140efa · outbound

This paper cites Ota: Optimal transport assignment for object detection.

What is YOLOv6? A Deep Insight into the Object Detection Model Ota: Optimal transport assignment for object detection

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:34:55.755657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 068f6fb5-bd32-4aa3-9303-1ea6426bc17c · outbound

This paper cites Varifocalnet: An iou-aware dense object detector.

What is YOLOv6? A Deep Insight into the Object Detection Model Varifocalnet: An iou-aware dense object detector

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:34:55.738971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c99e7a7a-4883-46df-b1fd-a41c39f48d54 · outbound

This paper cites SIoU Loss: More Powerful Learning for Bounding Box Regression.

What is YOLOv6? A Deep Insight into the Object Detection Model SIoU Loss: More Powerful Learning for Bounding Box Regression

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.350839Z

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Observation f84f85a0-b405-41b1-931a-3f87361224a5 · outbound

This paper cites Generalized intersection over union: A metric and a loss for bounding box regression.

What is YOLOv6? A Deep Insight into the Object Detection Model Generalized intersection over union: A metric and a loss for bounding box regression

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.355680Z

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Observation 9b4b3547-85ca-4db7-ac27-6be7e6d686af · outbound

This paper cites Focal loss for dense object detection.

What is YOLOv6? A Deep Insight into the Object Detection Model Focal loss for dense object detection

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:34:55.712458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 92aad1ce-3cd0-4541-b31c-c747ef5e6b4d · outbound

This paper cites Generalized focal loss: Learning qualified and distributed bounding boxes for dense object detection.

What is YOLOv6? A Deep Insight into the Object Detection Model Generalized focal loss: Learning qualified and distributed bounding boxes for dense object detection

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:34:55.696077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 07aca918-b385-4960-bd3c-96b7ef52ff18 · outbound

This paper cites PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions.

What is YOLOv6? A Deep Insight into the Object Detection Model PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.369556Z

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Observation 5222b5ca-f904-472b-87ec-44def7efaec5 · outbound

This paper cites Generalized focal loss v2: Learning reliable localization quality estimation for dense object detection.

What is YOLOv6? A Deep Insight into the Object Detection Model Generalized focal loss v2: Learning reliable localization quality estimation for dense object detection

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:34:55.680693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 994b64c0-6aff-4ce8-b07d-daa252151522 · outbound

This paper cites Re-parameterizing Your Optimizers rather than Architectures.

What is YOLOv6? A Deep Insight into the Object Detection Model Re-parameterizing Your Optimizers rather than Architectures

Reference 63

Resolution: verified exact; local_arxiv, observed 2026-08-11T13:34:55.442667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3960d289-5288-4712-bc5b-a8f71dae2a60 · outbound

This paper cites Yolov6 object detection – paper explanation and inference, 2022.

What is YOLOv6? A Deep Insight into the Object Detection Model Yolov6 object detection – paper explanation and inference, 2022

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:34:55.665894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2a853aae-9a6d-486d-b10f-81ba0d1e5b02 · outbound

This paper cites Deployment of ai-based rbf network for photovoltaics fault detection procedure.

What is YOLOv6? A Deep Insight into the Object Detection Model Deployment of ai-based rbf network for photovoltaics fault detection procedure

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.388881Z

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Observation 4b1e0504-d240-4eed-92ce-10021d6b828c · outbound

This paper cites Domain modelling for a lightweight convolutional network focused on automated exudate detection in retinal fundus images.

What is YOLOv6? A Deep Insight into the Object Detection Model Domain modelling for a lightweight convolutional network focused on automated exudate detection in retinal fundus images

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.393497Z

Source-reported events for the cited work

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Observation 22c94494-c340-4882-a973-bee0bdc83c65 · outbound

This paper cites Child emotion recognition via custom lightweight cnn architecture.

What is YOLOv6? A Deep Insight into the Object Detection Model Child emotion recognition via custom lightweight cnn architecture

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:34:55.631435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 706f9583-d726-4808-ac75-c0ce2cfbfaa3 · outbound

This paper cites You Only Learn One Representation: Unified Network for Multiple Tasks.

What is YOLOv6? A Deep Insight into the Object Detection Model You Only Learn One Representation: Unified Network for Multiple Tasks

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-11T13:34:55.239866Z

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Pith citing papers

Observation be17bab0-10dc-4d3d-b1ab-ad02d38fe017 · inbound

Performance of YOLOv7 in Kitchen Safety While Handling Knife cites this paper.

Performance of YOLOv7 in Kitchen Safety While Handling Knife What is YOLOv6? A Deep Insight into the Object Detection Model

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-10T21:15:57.417539Z

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Unavailable: canonical work link unavailable.

Observation 801874fe-a331-4a86-91ef-2ffe743afbab · inbound

YOLOv4: A Breakthrough in Real-Time Object Detection cites this paper.

YOLOv4: A Breakthrough in Real-Time Object Detection What is YOLOv6? A Deep Insight into the Object Detection Model

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-08-08T23:20:54.309094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.