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Paper Citation Record · LEDGER

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

As of 19 August 2026, this Paper Citation Record lists 71 of 71 outbound references and 0 inbound Pith citation observations for arXiv:2504.11995.

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

pith.paper-citation-record.v1
2504.11995 v1

Coverage vector

measured 71 of 71 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:40:32.619133Z

measured 71 of 71 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

71 of 71 outbound references displayed

  • verified exact0
  • verified fuzzy39
  • unresolved32
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T12:40:33.699379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.261934Z digest=sha256:564013e49c18cb1910bd3ee93267eb9d3057345dc91a89eb73d4e98b432c0ed9

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.267564Z digest=sha256:dd3ff5a4fbcb3d5c424c3ac0bd54c414691a9478c51d797d91cbd5feecd2c5c7

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.273160Z digest=sha256:1ce331e1f2b507dae26a815dbc13251c3d9e845f78f9bd1e14e75f1525621b37

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.279093Z digest=sha256:179150a3963e9dc802bdd43cdbcb54995d0bcdde5666059dd95fdf83583e6ebb

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.286031Z digest=sha256:151cbfd34931052e0271e1df8cffddbd10f4ff913e2d6ecfb78f1f11f2f1b8f9

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.290944Z digest=sha256:b3d2810e98a4b5abe11aa0bdde8d347c30555c7aa0c9bc2bb61e5d534f6f2269

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.296464Z digest=sha256:027341cfaf3164c2c98300a2dd42a139c3fbbdb11d11d83adebf5d2a6e14b709

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.300947Z digest=sha256:d020b6eccf0ab1ec0888750ee253a6b458e91eb15981e8190a562d7df98d7846

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.305525Z digest=sha256:037218242887c9087f9cbd49a935464c65a943d007657192deafc95f20e5b432

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.309852Z digest=sha256:9376fff96a82c76a6ba6a2609f1fc1e6b6ac03ff42844aee77236b60e1da47e7

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

Resolution
unresolved
no resolver link, observed 2026-08-16T12:40:32.315064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.315064Z digest=sha256:706c4beedf95c57468dc7987fd341295beb5a59224eb095104b0008b8dfb2e76

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.319641Z digest=sha256:78c9efeeecf676c235497fa84ef0d1980cbae8b9f4838906a7218c4d5ef858bc

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.323866Z digest=sha256:b2fb2a02d0cd4e43f2d5abe010a586590907e519c2b5028307dabc1d8a28a5f8

Observation 1f62e572-441a-4d4a-8c1d-157c0aa99c00 · outbound

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.329403Z digest=sha256:759b6d9b2071be9c2b328c65aef999a9f707bd3e30d473838feb70339ed2fb0d

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.334640Z digest=sha256:aad3ab0182cf708e52c0983283314cb7028c288f327fce39028b557dbb542c13

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.340979Z digest=sha256:b85ba4dfecc79c90cc83c5f19682d95de0481daad05dcd2613ebef6aff66e4b1

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.346489Z digest=sha256:69e2be52ed9fff91579e02ab8983cf631cbae82f0c98bec73e46e353ff218f04

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.350942Z digest=sha256:35d13e7fc90129cada57c6a81788de370abbe089bf023dcc5553917e2abebf94

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.355444Z digest=sha256:bb6de643e44d78b6d8b5323ea5a3948d6398b09393258c193858d54ca4d51ab0

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.360960Z digest=sha256:1cbf26a43be22bddad96557c73e55fc4060e5d25f7584b5dd82ec54b1248878d

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.365702Z digest=sha256:f72c2a810001c72025710a7ea0483ec82baed29c739c2b8ae2a45fe80d4be593

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.371035Z digest=sha256:8a8ca54793e43ab5829817475773d87fc4eb5672732469606f5e226e4e7c8333

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

Resolution
unresolved
no resolver link, observed 2026-08-16T12:40:32.374906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.374906Z digest=sha256:4e03122448b225e6e55721dee2ed8766e63a5dc4fbb2c39dba86ddf13bdaee52

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.380342Z digest=sha256:60c782cf74c39c898b0fe3192b192408cc289b28ec125842b889f4b695bdb356

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.384801Z digest=sha256:7746bf96797112ce0d6b16188ea1e9c816cda7ad839aaf72a5f0ea8c4f0bb953

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.388971Z digest=sha256:a86fa2593537e6dea656d4b722680ab67820d0e6e66e041f61a396a74ee3d9c4

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.393547Z digest=sha256:59a7018342def75af315b2eed3abad027b2fd2a63c433cdeef635e9f5021d5b4

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.398416Z digest=sha256:4665174d9c6cc9ab82b01237d4ae674572190bedaf36e620d24a803664ae031a

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.402859Z digest=sha256:178d2ec573f370ff495b6469d3d0a410412b9a767f73020a574897d9d6bd038d

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.407606Z digest=sha256:6e51b61417294cf2e093d4945cab6e652855a356b28abad5f26774893559d887

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.412594Z digest=sha256:067b90e70ce81217f7211c0350de894daee91a20cb47be5d528b75e2c9a29102

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.417646Z digest=sha256:854d7dce4ec569f4f71d7dde2c2878ad5700fb5f92cd78de57cd425569767f57

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.422698Z digest=sha256:b38e0c4134b1f295bed189c6bf7d30c76e62306e5a43a4e7140507b96db955a9

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.428369Z digest=sha256:3482b536c035f026ffe86e4218cfa94f834ebba207e46c0f66c2741bd5f4d48e

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

Resolution
unresolved
no resolver link, observed 2026-08-16T12:40:32.433671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.433671Z digest=sha256:3e566ba4d2876e366ab58ba61aa41480f276af84abda27104dc084435722f2e5

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.438206Z digest=sha256:b8d11dd88f859722b86c8bfda23bd6d51c326e9dbf5f9f398141da74cd28a391

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.443598Z digest=sha256:326d92bec11c340e913954a8ea72232c08068fd3f617fe915dc82ad6012bd4b5

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.448627Z digest=sha256:22e38f8d4325dc35fe8f164f78bb7d226f3b6791438124c25127f9beb01fc8cd

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.453650Z digest=sha256:51d73b05a269f44d0998a4d86e80bb34420c8cd49f643447da966f391185d36e

Observation 5347aa54-4bab-48e5-bb18-ca056eca3747 · outbound

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

Resolution
unresolved
no resolver link, observed 2026-08-16T12:40:32.458006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.458006Z digest=sha256:fc086b7325d056e8f57d7456e18b383fd1ffac3269909acf3e56c46dc635b4a3

Observation cc3be276-c0eb-4efb-91c3-e61e123c1317 · outbound

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.462578Z digest=sha256:446f1d9d2d7b66b04280899bd23a0a61fc3d8c055829975b7ff71e686246185a

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.467667Z digest=sha256:182e7733fceb357d5347a7479984e78ded9586d83d8ac1358541f2c28bb49a38

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.473069Z digest=sha256:eca42837d8707fd7a8a40e40d7a6ba2223192b31aae827f944374923fedbc474

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.478025Z digest=sha256:22e735f362a88a0451d136a367b22f1bd6e61eb2fced59dce9784c9b48f0a01b

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.483920Z digest=sha256:b03d1fcfe3abdcd70c810c4887805b827235d99d7f2e0a229d2f6db103ddd957

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.488596Z digest=sha256:6064b4a912b01085640e2b6111dd18ed5c3e1582fbc648acdd13c025c91c3556

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

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.494000Z digest=sha256:320bdfefcad770b3555a5a68369e1c149bf92e713d6f73e3ba0e73485536373e

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.498770Z digest=sha256:889f6ee3035972be3b489540e84e2e049070395e2db5fc9d04fbfad13b65f358

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.503788Z digest=sha256:d0148b8efcf78c20f89b0792c7f274c405064e94d463e2c094feffe4d5368caa

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.509217Z digest=sha256:06df897a9e139f6edf0d81527f181bbac879d98d394c42ca59d94e779803f898

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:32.513659Z digest=sha256:8ead7bde00c57d713a90ade2e9df0112c011b3eb0b0a6dcc095663b889e4abc2

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.520020Z digest=sha256:b00608c9c4a9833eb2a62b078a452f6d268e79650acfd61f5fd3e1034de8abb6

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.525047Z digest=sha256:a830c00b8eaba0fbb04d873456fc7536fc54ee7c757b6acb6c4dd7b8ae7e0d73

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.530962Z digest=sha256:f7959437e776aa043aee914d4c8d2e10b555edf7dff5bcc2564985217a21b9cf

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.536762Z digest=sha256:7cb7614058063b2443b0ce7d1f38093f7c4b7aca8b66cfa314385c7692347547

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.542170Z digest=sha256:ecad8beb723f31082a7d4dd07ca72ebc1261aecd5e8a6d9bfee89c4cb97ebdc6

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.546921Z digest=sha256:c2b6016a882b0ae856ea2ac2d2f30f680f696845664544738e98d5a4453aeb4c

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.551883Z digest=sha256:3fedec303425b6295e80848fe4b191c742d4e624c3b6d3c9c4981cf48a26fa7c

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.557462Z digest=sha256:8024604385918766745baad164f95eec2dbfdac5328b0b3a1f38afc7ce0cd1ac

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.561978Z digest=sha256:425378cfc68d262287236a7837aac0f6bebe8b3937847d45017b4b25070042ea

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.567556Z digest=sha256:d3ff6bf9d8c3ac8543525e60d1c10bf4b251badea1ad6193f9ae521e2b768e1b

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.572770Z digest=sha256:c040337f9d2568ed5c0f484bee8e617d0cb20d563aa12a62d98a8dba15f79bd8

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.577225Z digest=sha256:6e249e6271da37956358e4297da6956a417f753db85397e676996b81c167727c

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.582161Z digest=sha256:3784f0bca5757798798b8eb6a75281c1794f9e2f2e68430f2539b497a66136ec

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.587944Z digest=sha256:5683bef307afec6cb84fbb4bffe66fc1de4ab63643bb6ee473ed3a8e5c4f85b4

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.592866Z digest=sha256:cc148de9245b4e59e2a5abd602df96415e35b5888c567b745ebf77e835f7b736

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.

source=pdf_text observed=2026-08-16T12:40:32.597691Z digest=sha256:e66949f3981be35f03452b96df8451c13518bc21be09e444a1ca47fb2ecc5bd1

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.602763Z digest=sha256:5526ada313eea9d881f7d093889eb4d12c38528bdbfb58d49a49ac8e80b8c437

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.

source=pdf_text observed=2026-08-16T12:40:32.607892Z digest=sha256:8033424317084f99ee0ba8104d5628be4a500eca69f39d5588a610ecb2404834

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T12:40:32.613504Z digest=sha256:0284421983f005ab6b6914a81595bd07fb8cec67c7e1f985e6960a081a2d24e9

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

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