Paper Citation Record · LEDGER

Drone Detection and Tracking with YOLO and a Rule-based Method

As of 15 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 1 inbound Pith citation observation for arXiv:2502.05292.

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

pith.paper-citation-record.v1
2502.05292 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:56:28.464967Z

measured 21 of 21 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T18:37:32.510633Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

20 of 20 outbound references displayed

verified exact1
verified fuzzy15
unresolved3
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 61d06ccf-a15d-4e4d-bf2b-2858b435d03f · outbound

This paper cites A Dataset of Infrared Images for Deep Learning based Drone Detection,.

Drone Detection and Tracking with YOLO and a Rule-based Method A Dataset of Infrared Images for Deep Learning based Drone Detection,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:56:28.764640Z

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 13746fe0-b992-43c0-aeb3-ec6421cfa5ff · outbound

This paper cites Faster R-CNN: Towards Real- Time Object Detection with Region Proposal Networks,.

Drone Detection and Tracking with YOLO and a Rule-based Method Faster R-CNN: Towards Real- Time Object Detection with Region Proposal Networks,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:56:28.751035Z

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 6d2c3058-31b0-4c10-b598-a1c89d4fff10 · outbound

This paper cites SSD: Single Shot MultiBox Detector,.

Drone Detection and Tracking with YOLO and a Rule-based Method SSD: Single Shot MultiBox Detector,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:56:28.737559Z

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 b481369c-cf3b-4f0e-a974-2d1038ca61e3 · outbound

This paper cites EfficientDet: Scalable and Efficient Object Detection,.

Drone Detection and Tracking with YOLO and a Rule-based Method EfficientDet: Scalable and Efficient Object Detection,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:56:28.723858Z

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 36595c29-4bf6-4a66-aa6c-a1c215f83344 · outbound

This paper cites Shore Livecams: A Maritime Dataset for Deep Learning based Object Detection,.

Drone Detection and Tracking with YOLO and a Rule-based Method Shore Livecams: A Maritime Dataset for Deep Learning based Object Detection,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:56:28.710616Z

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 846bb0b3-7612-4cac-b2b1-72a3b36c3e59 · outbound

This paper cites CNN based Drone Detection in Infrared Images,.

Drone Detection and Tracking with YOLO and a Rule-based Method CNN based Drone Detection in Infrared Images,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:56:28.697261Z

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 2ae73930-010c-46a9-8290-97767e5d0de2 · outbound

This paper cites Real-Time Detection for Small UAVs: Combining YOLO and Multi-frame Motion Analysis.

Drone Detection and Tracking with YOLO and a Rule-based Method Real-Time Detection for Small UAVs: Combining YOLO and Multi-frame Motion Analysis

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-08T19:56:28.558580Z

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 2d67a4a9-e678-4f96-8d78-b173b01c49fc · outbound

This paper cites GStreamer: open source multimedia framework.

Drone Detection and Tracking with YOLO and a Rule-based Method GStreamer: open source multimedia framework

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:56:28.684133Z

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 d85273ae-3dfc-46c2-a13e-11ff9c0d51e9 · outbound

This paper cites Docker: lightweight linux containers for consistent devel- opment and deployment.

Drone Detection and Tracking with YOLO and a Rule-based Method Docker: lightweight linux containers for consistent devel- opment and deployment

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:56:28.671525Z

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 56ec6382-61ea-43f1-a7f9-e126e4a51685 · outbound

This paper cites LabelImg,.

Drone Detection and Tracking with YOLO and a Rule-based Method LabelImg,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:56:28.658111Z

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 f986bdf9-6c40-46ba-924f-568b4e102afd · outbound

This paper cites The Pascal Visual Object Classes (VOC) Challenge,.

Drone Detection and Tracking with YOLO and a Rule-based Method The Pascal Visual Object Classes (VOC) Challenge,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:56:28.644613Z

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 befad8a3-9407-46af-a614-30dfd84af316 · outbound

This paper cites ultralytics/yolov5: v3.1 - Bug Fixes and Performance Improvements,.

Drone Detection and Tracking with YOLO and a Rule-based Method ultralytics/yolov5: v3.1 - Bug Fixes and Performance Improvements,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-08T19:56:28.431992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a707601d-5b82-4345-8b78-d903a1b26d4e · outbound

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

Drone Detection and Tracking with YOLO and a Rule-based Method YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-08T19:56:28.436450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae51a70f-67e6-4f94-b50c-a88db69244c3 · outbound

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

Drone Detection and Tracking with YOLO and a Rule-based Method YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-08T19:56:28.440917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0ee36c3-c469-4818-9756-903abc7dc7e8 · outbound

This paper cites Deep Learning for Image Enhancement,.

Drone Detection and Tracking with YOLO and a Rule-based Method Deep Learning for Image Enhancement,

Reference 15

Resolution: malformed identifier; doi_truncated, observed 2026-08-08T19:56:28.500261Z

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 cac9c486-2309-45fa-9862-954e862f1aca · outbound

This paper cites CBAM: Convolutional Block Attention Module,.

Drone Detection and Tracking with YOLO and a Rule-based Method CBAM: Convolutional Block Attention Module,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:56:28.630092Z

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 e432e9f3-fbb4-4e7f-b0a6-2efd1a6c2259 · outbound

This paper cites Attention is All you Need,.

Drone Detection and Tracking with YOLO and a Rule-based Method Attention is All you Need,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:56:28.615146Z

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 dc9b8308-3f12-43b1-b4d9-c8dd4b037c00 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale,.

Drone Detection and Tracking with YOLO and a Rule-based Method An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:56:28.601210Z

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 9b8520a3-ca2e-4bff-9f06-c74d4663fb9b · outbound

This paper cites A Simple Single-Scale Vision Transformer for Object Detection and Instance Segmentation,.

Drone Detection and Tracking with YOLO and a Rule-based Method A Simple Single-Scale Vision Transformer for Object Detection and Instance Segmentation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:56:28.586887Z

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 0a928730-33ec-4a9b-816f-618c3925e277 · outbound

This paper cites Swin Transformer: Hierarchical Vision Transformer using Shifted Windows,.

Drone Detection and Tracking with YOLO and a Rule-based Method Swin Transformer: Hierarchical Vision Transformer using Shifted Windows,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:56:28.572917Z

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.

Pith citing papers

Observation 5200c768-1fe9-424d-a71c-47580f298af8 · inbound

WAVE-DETR Multi-Modal Visible and Acoustic Real-Life Drone Detector cites this paper.

WAVE-DETR Multi-Modal Visible and Acoustic Real-Life Drone Detector Drone Detection and Tracking with YOLO and a Rule-based Method

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T18:37:32.510633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.