Paper Citation Record · LEDGER

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures

As of 15 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2509.05490.

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

pith.paper-citation-record.v1
2509.05490 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T05:27:54.277336Z

measured 37 of 37 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 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

37 of 37 outbound references displayed

verified exact7
verified fuzzy20
unresolved10
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ab46fe66-5045-49db-b95d-4849affdb3a4 · outbound

This paper cites Real-Time Flying Object Detection with YOLOv8.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures Real-Time Flying Object Detection with YOLOv8

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T05:27:54.128484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08073b28-8453-45e3-8432-83e401f7b150 · outbound

This paper cites A YOLO-Based Traffic Counting System.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures A YOLO-Based Traffic Counting System

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.829169Z

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 89fdc094-22e0-41b6-b9c6-cc60a4204869 · outbound

This paper cites YOLO V3 + VGG16-based automatic operations monitoring and analysis in a manufacturing workshop under Industry 4.0.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures YOLO V3 + VGG16-based automatic operations monitoring and analysis in a manufacturing workshop under Industry 4.0

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.816407Z

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 e6d13988-266d-4d65-8646-007faa9c6a72 · outbound

This paper cites YOLO-Pose: Enhancing YOLO for Multi Person Pose Estimation Using Object Keypoint Similarity Loss.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures YOLO-Pose: Enhancing YOLO for Multi Person Pose Estimation Using Object Keypoint Similarity Loss

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-05T05:27:54.555867Z

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Observation 230112d5-5a50-44f9-b14c-9dc650b58e40 · outbound

This paper cites A Comprehensive Survey on Transfer Learning.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures A Comprehensive Survey on Transfer Learning

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.803818Z

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 20b5f9dc-aace-4e99-bc86-c203c227dd57 · outbound

This paper cites How transferable are features in deep neural networks?.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures How transferable are features in deep neural networks?

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T05:27:54.150634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b02a39d-43a2-4336-a3a7-7b7a183f09b8 · outbound

This paper cites Microsoft COCO: Common Objects in Context.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures Microsoft COCO: Common Objects in Context

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T05:27:54.155459Z

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Unavailable: canonical work link unavailable.

Observation b2af1396-d0e6-4fa3-9dc4-c7a3153bca2c · outbound

This paper cites A Review and Implementation of Object Detection Models and Optimizations for Real-time Medical Mask Detection during the COVID-19 Pandemic.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures A Review and Implementation of Object Detection Models and Optimizations for Real-time Medical Mask Detection during the COVID-19 Pandemic

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.791081Z

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 b52d53c0-2292-4ed9-8956-487106964095 · outbound

This paper cites Improving Vehicle Detection in Challenging Datasets: YOLOv5s and Frozen Layers Analysis.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures Improving Vehicle Detection in Challenging Datasets: YOLOv5s and Frozen Layers Analysis

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.778054Z

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 2b9bf500-4583-4f98-86b1-f92f93feae27 · outbound

This paper cites AutoFreeze: Automatically Freezing Model Blocks to Accelerate Fine-tuning.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures AutoFreeze: Automatically Freezing Model Blocks to Accelerate Fine-tuning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T05:27:54.167400Z

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Observation d462edb3-af16-4089-bd76-e6206c0da3d3 · outbound

This paper cites PipeTransformer: Automated Elastic Pipelining for Distributed Training of Transformers.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures PipeTransformer: Automated Elastic Pipelining for Distributed Training of Transformers

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T05:27:54.171488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 266e3cd7-344c-49fc-9e95-6a5462a6349b · outbound

This paper cites Ultralytics YOLO.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures Ultralytics YOLO

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.765345Z

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 b21d4648-7d76-410c-a274-e269461ffba3 · outbound

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

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures YOLOv10: Real-Time End-to-End Object Detection

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T05:27:54.179520Z

Source-reported events for the cited work

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Observation c294e692-6a6a-4055-bd01-84cc48361e61 · outbound

This paper cites Egeria: Efficient DNN Training with Knowledge-Guided Layer Freezing.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures Egeria: Efficient DNN Training with Knowledge-Guided Layer Freezing

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-05T05:27:54.469658Z

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 642b6807-4124-49ef-a86d-59f6a8b8d078 · outbound

This paper cites Training Acceleration Method Based on Parameter Freezing.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures Training Acceleration Method Based on Parameter Freezing

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.752581Z

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 c6a6faad-0d7f-4226-8666-33b01d4f8b53 · outbound

This paper cites FreezeNet: Full Performance by Reduced Storage Costs.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures FreezeNet: Full Performance by Reduced Storage Costs

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-05T05:27:54.450360Z

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 a4ee801c-9848-4c6c-bcd8-16a86c729039 · outbound

This paper cites Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T05:27:54.196168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3140ee8f-751c-4738-b7c2-02de771d9ea3 · outbound

This paper cites Features Exploitation of YOLOv5-Based Freeze Backbone for Perfor mance Improvement of UAV Object Detection.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures Features Exploitation of YOLOv5-Based Freeze Backbone for Perfor mance Improvement of UAV Object Detection

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.740107Z

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 5459cfc1-d085-4357-94fb-bee15d52a77e · outbound

This paper cites Status Recognition Using Pre-Trained YOLOv5 for Sustainable Human-Robot Collaboration (HRC) System in Mold Assembly.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures Status Recognition Using Pre-Trained YOLOv5 for Sustainable Human-Robot Collaboration (HRC) System in Mold Assembly

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.726086Z

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 893b1239-8853-49ce-97ca-757aea6155c9 · outbound

This paper cites Application of Three Transfer Learning Methods Based on YOLOv8 for Object Recognition in Architectural Drawings.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures Application of Three Transfer Learning Methods Based on YOLOv8 for Object Recognition in Architectural Drawings

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.712365Z

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 41efbfab-0cf1-47c0-aa28-be603a285669 · outbound

This paper cites Fine-Tuning Without Forgetting: Adaptation of YOLOv8 Preserves COCO Performance.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures Fine-Tuning Without Forgetting: Adaptation of YOLOv8 Preserves COCO Performance

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-05T05:27:54.417571Z

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 1fb78f7d-9db2-4d86-9276-1415d3e08ce2 · outbound

This paper cites CSPNet: A New Backbone that can Enhance Learning Capability of CNN.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures CSPNet: A New Backbone that can Enhance Learning Capability of CNN

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-05T05:27:54.398553Z

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 fcaac86c-66d9-4eb1-b059-7ab1882473f1 · outbound

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

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures YOLOv4: Optimal Speed and Accuracy of Object Detection

Reference 23

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Source-reported events for the cited work

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Observation 651f9a99-7da8-4036-9aa4-cbb85ec5f288 · outbound

This paper cites A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOvl to YOLOv8 and YOLO-NAS.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOvl to YOLOv8 and YOLO-NAS

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.698942Z

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

Observation a34c55ab-d903-451b-992c-6fee773b33ae · outbound

This paper cites InsPLAD: A Dataset and Benchmark for Power Line Asset Inspection in UAV Images.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures InsPLAD: A Dataset and Benchmark for Power Line Asset Inspection in UAV Images

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.685930Z

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

Observation f4cf39f2-cd41-4b94-bab6-ff09e9891e62 · outbound

This paper cites A YOLO Annotated 15-class Ground Truth Dataset for Substation Equipment.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures A YOLO Annotated 15-class Ground Truth Dataset for Substation Equipment

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.673290Z

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 6e07c2c5-7720-47d7-9f4a-43a3fe8af554 · outbound

This paper cites VALID: A Comprehensive Virtual Aerial Image Dataset.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures VALID: A Comprehensive Virtual Aerial Image Dataset

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.660884Z

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 15b8c3b7-57d6-43e2-9572-2d06690bd39f · outbound

This paper cites Deep Learning-Based Bird's Nest Detection on Transmission Lines Using UAV Imagery.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures Deep Learning-Based Bird's Nest Detection on Transmission Lines Using UAV Imagery

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.647872Z

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 70f0705b-7ce9-4afa-9d03-822c981b2dcb · outbound

This paper cites Review and analysis of synthetic dataset generation methods and techniques for application in computer vision.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures Review and analysis of synthetic dataset generation methods and techniques for application in computer vision

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.634274Z

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 a9b6b4c9-cc5d-4db1-81ad-14e3a2985a3b · outbound

This paper cites Explore the power of synthetic data on few-shot object detection.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures Explore the power of synthetic data on few-shot object detection

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.621117Z

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 15d956a8-295f-4112-a86e-81e55e7f7fbd · outbound

This paper cites Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.608157Z

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

Observation a6749701-549b-4c46-be19-fae833cd0361 · outbound

This paper cites YOLO-V8-CAM.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures YOLO-V8-CAM

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.595310Z

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

Observation e8943bde-dda1-4a70-91fd-0d7b4817e1ac · outbound

This paper cites The Golden Ratio of Learning and Momentum.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures The Golden Ratio of Learning and Momentum

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-08-05T05:27:54.366654Z

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 09ff74e7-9b38-4195-b9e4-0aa6efd226cc · outbound

This paper cites On the importance of initialization and momentum in deep learning.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures On the importance of initialization and momentum in deep learning

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T05:27:54.581718Z

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 fdbdbb6a-40b4-46dd-a8c2-c809f295772d · outbound

This paper cites The instabilities of large learning rate training: a loss landscape view.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures The instabilities of large learning rate training: a loss landscape view

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-08-05T05:27:54.344837Z

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 9a1416f7-d4e7-47b2-9b6f-db48eb364ab6 · outbound

This paper cites Identifying and attacking the saddle point problem in high-dimensional non-convex optimization.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures Identifying and attacking the saddle point problem in high-dimensional non-convex optimization

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-05T05:27:54.273487Z

Source-reported events for the cited work

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Observation 0d3a21c5-11c8-40d5-8a55-b371c9e4e0e9 · outbound

This paper cites Visualizing the Loss Landscape of Neural Nets.

An Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures Visualizing the Loss Landscape of Neural Nets

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-05T05:27:54.277336Z

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Unavailable: canonical work link unavailable.

Pith citing papers

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