A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions | Paper Citation Record

Observation da026c96-3174-499e-b1f2-2372f9da0c6d · outbound

This paper cites Deep multi-modal object detection and semantic segmentation for autonomous driving: Datasets, methods, and challenges.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Deep multi-modal object detection and semantic segmentation for autonomous driving: Datasets, methods, and challenges

Reference 1

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Observation 437f7275-f563-4a74-8f2f-cd05c672a06a · outbound

This paper cites A review and comparative study on probabilistic object detection in autonomous driving.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions A review and comparative study on probabilistic object detection in autonomous driving

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.682899Z

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Observation 72b4b6e9-e32a-4ec1-b371-2bf9218a00fe · outbound

This paper cites 3d object detection for autonomous driving: A comprehensive survey.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions 3d object detection for autonomous driving: A comprehensive survey

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.666358Z

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Observation 7e67fb97-24c8-41df-9248-c3dc09ec43eb · outbound

This paper cites A review on object detection based on deep convolutional neural networks for autonomous driving.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions A review on object detection based on deep convolutional neural networks for autonomous driving

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.649643Z

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Observation 1d4de671-21a2-474c-a83d-6b911558d7f2 · outbound

This paper cites A review of machine learning and deep learning for object detection, semantic segmentation, and human action recognition in machine and robotic vision.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions A review of machine learning and deep learning for object detection, semantic segmentation, and human action recognition in machine and robotic vision

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.633382Z

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Observation 5549f890-976f-4ee2-ac16-75c1e2f11924 · outbound

This paper cites Object detection recognition and robot grasping based on machine learning: A survey.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Object detection recognition and robot grasping based on machine learning: A survey

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.614688Z

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Observation 7fbffa19-e40f-48a1-83ce-7e36c1d04741 · outbound

This paper cites The object detection, perspective and obstacles in robotic: a review.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions The object detection, perspective and obstacles in robotic: a review

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.598617Z

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Observation f5f23d87-d950-4e65-9291-d9d4d5a3a670 · outbound

This paper cites Object detection, classification and tracking methods for video surveillance: A review.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Object detection, classification and tracking methods for video surveillance: A review

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.582063Z

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Observation d5a10d2d-d5c2-4236-b31f-8f829d00e583 · outbound

This paper cites A review on object detection and tracking in video surveillance.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions A review on object detection and tracking in video surveillance

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.565466Z

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Observation b1e34b92-484d-40a5-b2cd-24093c8618bc · outbound

This paper cites A study on video surveillance system for object detection and tracking.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions A study on video surveillance system for object detection and tracking

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.548707Z

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Observation d7856009-b019-43b6-adfc-33b72abfddc2 · outbound

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

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions You only look once: Unified, real-time object detection

Reference 11

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Observation 0a7f9b98-8902-439b-86b2-b6eea1dc8034 · outbound

This paper cites Yolo9000: better, faster, stronger.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Yolo9000: better, faster, stronger

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.319641Z

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Observation 858dfbb8-6c91-4699-860b-a8dfe68cdfdd · outbound

This paper cites YOLOv3: An Incremental Improvement.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions YOLOv3: An Incremental Improvement

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.323866Z

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

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions YOLOv4: Optimal Speed and Accuracy of Object Detection

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.329403Z

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Observation 72f07d04-0a99-48a6-ad84-ba6c0a4a6d66 · outbound

This paper cites Ultralytics yolov5, 2020.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Ultralytics yolov5, 2020

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.334640Z

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Observation 9f57da44-77cf-4b35-96e6-d4b4b670b058 · outbound

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

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.340979Z

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Observation 037ffa5b-792b-4ee1-abf4-0119e403caef · outbound

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

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.346489Z

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Observation 4095c6f4-0af6-4454-b027-eb176eef3bd3 · outbound

This paper cites Ultralytics yolov8, 2023.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Ultralytics yolov8, 2023

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.350942Z

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Observation b83e8b8b-d14d-47ad-ab52-e91956023037 · outbound

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

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.355444Z

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Observation 31e4548d-5041-4597-a171-0e6688fd2493 · outbound

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

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions YOLOv10: Real-Time End-to-End Object Detection

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.360960Z

Source-reported events for the cited work

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Observation 35f89233-8471-49c8-9bff-6e1ef06f76e1 · outbound

This paper cites Ultralytics yolo11, 2024.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Ultralytics yolo11, 2024

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.365702Z

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Observation fccf4db5-d8ee-45c8-aac9-136da3e66b50 · outbound

This paper cites Eva-02: A visual representation for neon genesis.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Eva-02: A visual representation for neon genesis

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.469928Z

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Observation fdab996b-ac92-4d2b-a0e2-40bb5098ceef · outbound

This paper cites Masked autoencoders are scalable vision learners.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Masked autoencoders are scalable vision learners

Reference 23

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Observation a57a3557-c3bd-403c-b2fe-8f402d80c8cf · outbound

This paper cites Vmamba: Visual state space model.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Vmamba: Visual state space model

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.441901Z

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Observation d1dc782c-c2be-4eda-b760-f49f332a80be · outbound

This paper cites Flashattention: Fast and memory-efficient exact attention with io-awareness.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Flashattention: Fast and memory-efficient exact attention with io-awareness

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.384801Z

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Observation a2151e69-6ed8-48de-99a2-39e24a97aab7 · outbound

This paper cites FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.388971Z

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Observation ff9cfa4e-5198-4c25-9692-ca53c3d991a5 · outbound

This paper cites YOLOv12: Attention-Centric Real-Time Object Detectors.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions YOLOv12: Attention-Centric Real-Time Object Detectors

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.393547Z

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Observation 0708ac42-000f-422f-b54a-e02320ba47a4 · outbound

This paper cites A comprehensive review of convolutional neural networks for defect detection in industrial applications.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions A comprehensive review of convolutional neural networks for defect detection in industrial applications

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.398416Z

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Observation 2abd21b6-e389-41d8-9dc4-79c65e0b8517 · outbound

This paper cites Linformer: Self-Attention with Linear Complexity.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Linformer: Self-Attention with Linear Complexity

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.402859Z

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Observation 341d04de-bdc5-4f70-887a-0c4a9e151410 · outbound

This paper cites Efficient attention: Attention with linear complexities.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Efficient attention: Attention with linear complexities

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.407606Z

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Observation 3008ff1c-bd06-4ca7-94cd-47dbd46b1a5d · outbound

This paper cites Transformers are rnns: Fast autoregressive transformers with linear attention.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Transformers are rnns: Fast autoregressive transformers with linear attention

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.412594Z

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Observation 04da8113-d29f-4a8e-afa9-e22ba4ca3db4 · outbound

This paper cites Rethinking Attention with Performers.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Rethinking Attention with Performers

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.417646Z

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Observation 8b93b8aa-98e0-44f4-91c3-4539390ce0be · outbound

This paper cites Nyströmformer: A nyström-based algorithm for approximating self-attention.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Nyströmformer: A nyström-based algorithm for approximating self-attention

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.422698Z

Source-reported events for the cited work

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Observation 3e40511a-c2ef-4852-aab5-52acc76253f5 · outbound

This paper cites Low-rank bottleneck in multi-head attention models.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Low-rank bottleneck in multi-head attention models

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.373817Z

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Observation 39dbb0b3-a4c9-4596-bbb1-7c5a15acf1a9 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Swin transformer: Hierarchical vision transformer using shifted windows

Reference 35

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Observation c87d0ffe-26c1-44a0-8e01-1f44a88dec4e · outbound

This paper cites Ccnet: Criss-cross attention for semantic segmentation.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Ccnet: Criss-cross attention for semantic segmentation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.347104Z

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Observation 88978550-847f-455f-8faa-fcb04c199487 · outbound

This paper cites Cswin transformer: A general vision transformer backbone with cross-shaped windows.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Cswin transformer: A general vision transformer backbone with cross-shaped windows

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.443598Z

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Observation fb1257c1-eab3-426c-b041-2f38de3d95de · outbound

This paper cites Going deeper with image transformers.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Going deeper with image transformers

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.319150Z

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Observation 59e48347-4fc4-426c-a43e-cf5bc114a888 · outbound

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

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Cspnet: A new backbone that can enhance learning capability of cnn

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.453650Z

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This paper cites Microsoft coco: Common objects in context.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Microsoft coco: Common objects in context

Reference 40

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This paper cites Ultralytics Website.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Ultralytics Website

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.279767Z

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Observation ca9ad750-bb89-4dbe-82a5-7b75ec91a33b · outbound

This paper cites YOLOv11: An Overview of the Key Architectural Enhancements.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions YOLOv11: An Overview of the Key Architectural Enhancements

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.467667Z

Source-reported events for the cited work

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Observation 3622c13e-9f3c-4029-9304-5df61a0990a7 · outbound

This paper cites What is YOLOv5: A deep look into the internal features of the popular object detector.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions What is YOLOv5: A deep look into the internal features of the popular object detector

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.473069Z

Source-reported events for the cited work

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Observation eb493d14-983e-484b-9597-242c32390e8f · outbound

This paper cites A Comprehensive Review on Autonomous Navigation.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions A Comprehensive Review on Autonomous Navigation

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.478025Z

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Observation 8bffab65-7203-4cc9-8d65-4b88842acbd2 · outbound

This paper cites Perception and navigation in autonomous systems in the era of learning: A survey.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Perception and navigation in autonomous systems in the era of learning: A survey

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.260918Z

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Observation 6a2ae7b1-b6d2-415d-8c34-821b10e2120d · outbound

This paper cites Object detection in traffic videos: A survey.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Object detection in traffic videos: A survey

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.242175Z

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Observation 2473055b-6a67-4494-961d-e2494e09367a · outbound

This paper cites A review on object detection in unmanned aerial vehicle surveillance.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions A review on object detection in unmanned aerial vehicle surveillance

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.224403Z

Source-reported events for the cited work

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Observation c88886bf-9aaa-4d0d-a879-ea3301b57bde · outbound

This paper cites Deep learning methods for object detection in smart manufacturing: A survey.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Deep learning methods for object detection in smart manufacturing: A survey

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.205587Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fdc740c4-c02e-45e1-8858-855802caebaa · outbound

This paper cites Comparative analysis of edge computing and edge devices: key technology in iot and computer vision applications.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Comparative analysis of edge computing and edge devices: key technology in iot and computer vision applications

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.187273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 67d056ba-f744-4d41-a3d3-1b6241dc7146 · outbound

This paper cites Synchronizing object detection: applications, advancements and existing challenges.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Synchronizing object detection: applications, advancements and existing challenges

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.169812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3c7404cf-f28a-40d0-a302-029fd451ad5b · outbound

This paper cites In-depth review of yolov1 to yolov10 variants for enhanced photo- voltaic defect detection.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions In-depth review of yolov1 to yolov10 variants for enhanced photo- voltaic defect detection

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.513659Z

Source-reported events for the cited work

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Observation 14423f4c-0cba-40b0-81ff-eefeb1740f4a · outbound

This paper cites Comparative performance evaluation of yolov5, yolov8, and yolov11 for solar panel defect detection.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Comparative performance evaluation of yolov5, yolov8, and yolov11 for solar panel defect detection

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.140576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 334f986e-a1b6-4253-ad7d-68690d26c55f · outbound

This paper cites Small object detection in diverse application landscapes: a survey.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Small object detection in diverse application landscapes: a survey

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.123746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1ae3851e-bcba-4651-bde2-cffcfc81133f · outbound

This paper cites An overview of machine learning within embedded and mobile devices–optimizations and applications.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions An overview of machine learning within embedded and mobile devices–optimizations and applications

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.107600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 743b2873-3ecc-4b7f-86ef-59b1ca61d75d · outbound

This paper cites A review of recent hardware and software advances in gpu-accelerated edge-computing single-board computers (sbcs) for computer vision.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions A review of recent hardware and software advances in gpu-accelerated edge-computing single-board computers (sbcs) for computer vision

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.091805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bf024e65-71cc-4f2e-b958-2c3aaf7f348f · outbound

This paper cites Compressing large language models using low rank and low precision decomposition.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Compressing large language models using low rank and low precision decomposition

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.076112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 55c07a64-8a50-481a-a72b-11f6a7cf0c64 · outbound

This paper cites Memory optimization at edge for distributed convolution neural network.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Memory optimization at edge for distributed convolution neural network

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.060030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 947cd4da-acd8-473c-940c-aca8c738d61e · outbound

This paper cites Efficient processing of convolutional neural networks on the edge: A hybrid approach using hardware acceleration and dual-teacher compression.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Efficient processing of convolutional neural networks on the edge: A hybrid approach using hardware acceleration and dual-teacher compression

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.045579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 79f65d71-7a72-4439-a148-05ff589e7fc0 · outbound

This paper cites Fasor: A fast tensor program optimization framework for efficient dnn deployment.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Fasor: A fast tensor program optimization framework for efficient dnn deployment

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.030121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 90a408c6-59a0-484f-9720-912a906eb038 · outbound

This paper cites Efficient convolutional networks learning through irregular convolutional kernels.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Efficient convolutional networks learning through irregular convolutional kernels

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:33.013632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d4a90277-5198-4059-bff0-0ae6bc6556d5 · outbound

This paper cites A survey on fpga-based sensor systems: towards intelligent and reconfigurable low-power sensors for computer vision, control and signal processing.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions A survey on fpga-based sensor systems: towards intelligent and reconfigurable low-power sensors for computer vision, control and signal processing

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:32.998247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 32da6830-01be-4b3c-8ecc-c37bb79df8be · outbound

This paper cites Optimizing transformers strategies for efficiency and scalability.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Optimizing transformers strategies for efficiency and scalability

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:32.980670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e1efc01d-8fd3-4116-af73-741c06b4fe8a · outbound

This paper cites Convolutional neural networks in medical image understanding: a survey.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Convolutional neural networks in medical image understanding: a survey

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:32.963371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c136c0f9-0d02-4a05-82bb-85cc5228ea76 · outbound

This paper cites Self-supervised learning: A succinct review.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Self-supervised learning: A succinct review

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:32.946246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1a218fe4-f07c-4f36-9d6e-aa8c838e185d · outbound

This paper cites A survey on deep semi-supervised learning.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions A survey on deep semi-supervised learning

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:32.931220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b9dbc225-1388-4370-9640-671043811585 · outbound

This paper cites A survey on self-supervised learning methods for domain adaptation in deep neural networks focusing on the optimization problems.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions A survey on self-supervised learning methods for domain adaptation in deep neural networks focusing on the optimization problems

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:32.915715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 645c6ade-0096-42bc-851a-29f03ff6c472 · outbound

This paper cites Neural architecture search: A survey.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Neural architecture search: A survey

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.597691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e6ebfb3-13a1-4074-8c8d-bde8e884fab9 · outbound

This paper cites Robotic vision: 3d object recognition and pose determination.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Robotic vision: 3d object recognition and pose determination

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:32.890249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 58d649e2-5829-4d8a-97d0-a0ee044c9675 · outbound

This paper cites Transformer-Based Autonomous Driving Models and Deployment-Oriented Compression: A Survey.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Transformer-Based Autonomous Driving Models and Deployment-Oriented Compression: A Survey

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.607892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8daaa640-eeff-4f75-a88c-21922473a0d5 · outbound

This paper cites A review of research on instance segmentation based on deep learning.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions A review of research on instance segmentation based on deep learning

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:32.874520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b9829a0c-7ccc-4f47-9275-aa6deeeefdc5 · outbound

This paper cites Panoptic Segmentation: A Review.

A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions Panoptic Segmentation: A Review

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:32.619133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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