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Paper Citation Record · LEDGER

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern

As of 7 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2507.02408.

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

pith.paper-citation-record.v1
2507.02408 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:35:03.430803Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+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

24 of 24 outbound references displayed

  • verified exact0
  • verified fuzzy17
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 76c25ac1-225d-42da-a8e4-d2d98a8db852 · outbound

This paper cites BoT- SORT: Robust Associations Multi-Pedestrian Tracking,.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern BoT- SORT: Robust Associations Multi-Pedestrian Tracking,

Reference 1

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 026894ef-f50a-4592-90dc-0f719509143e · outbound

This paper cites Enhancing Thermal MOT: A Novel Box Association Method Leveraging Thermal Identity and Mo- tion Similarity, 2024.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern Enhancing Thermal MOT: A Novel Box Association Method Leveraging Thermal Identity and Mo- tion Similarity, 2024

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:35:06.779415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation f32f160f-7e3a-4e31-987c-14813ccb035a · outbound

This paper cites Simple online and realtime tracking.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern Simple online and realtime tracking

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:35:06.599531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation d9cd17fe-cb61-4f08-9209-ce0608ba8f9a · outbound

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

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern YOLOv4: Optimal Speed and Accuracy of Object Detection

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T20:35:01.342948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:35:01.342948Z digest=sha256:1a196949c80f19fdf91f17c8a54d8ad576c7d57f35e17c2cd071451b8acba43f

Observation 09a2d236-cc7f-42ed-8b8a-4f7757bec753 · outbound

This paper cites Ther- mal pedestrian multiple object tracking challenge (tp-mot).

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern Ther- mal pedestrian multiple object tracking challenge (tp-mot)

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:35:06.445823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:35:01.488887Z digest=sha256:36add716abd7bb360734acb7faec9098768d0fd6b036fe3aab217538259ad365

Observation 815ee0a7-7210-4fab-8de1-553000407c0f · outbound

This paper cites Fast R-CNN.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern Fast R-CNN

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:35:06.290645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 82076b90-7fd5-4644-af8a-546594faba25 · outbound

This paper cites Rich Feature Hierarchies for Accurate Object Detec- tion and Semantic Segmentation.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern Rich Feature Hierarchies for Accurate Object Detec- tion and Semantic Segmentation

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:35:06.101871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:35:01.825259Z digest=sha256:5252bafb5999ba67f03e0ee22927f8a2ef8b8605aa738de916df6bf0e0214ca9

Observation dfc13e13-fdb3-4498-897a-8e0e1bd025f8 · outbound

This paper cites Multispectral pedestrian detection: Benchmark dataset and baseline.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern Multispectral pedestrian detection: Benchmark dataset and baseline

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:35:05.921268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 31ea39e3-80da-4acb-a7a2-11d8b7293305 · outbound

This paper cites Ultralytics YOLO, 2023.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern Ultralytics YOLO, 2023

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:35:05.761550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation de7cd6eb-a4d8-4178-b767-ae9bf290e71d · outbound

This paper cites an unresolved cited work.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-08-06T20:35:05.571599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:35:02.198470Z digest=sha256:47f692756e7a3e58b9af67e5e6016c8827e830d9c785215846baf24c724157ec

Observation 09318e20-aa8c-4d4b-99a3-d9e43f4b97a4 · outbound

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

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T20:35:02.201353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:35:02.201353Z digest=sha256:9b573333badbe5a32d5a0ae0573f7254e8e82b4f6dcbaae92ee382a86530d88a

Observation 253c46cd-a8a7-4fbd-90d6-432ab581a9fd · outbound

This paper cites PTB-TIR: A Thermal Infrared Pedestrian Tracking Benchmark.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern PTB-TIR: A Thermal Infrared Pedestrian Tracking Benchmark

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:35:05.412640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:35:02.245603Z digest=sha256:42e1ccdecaf834186f0ad23ab42e979e4e3de043a975688352ee7abe2618006e

Observation 0c0f9965-0ef5-4f47-a26e-f66d2aef720c · outbound

This paper cites an unresolved cited work.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-06T20:35:05.207417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:35:02.344116Z digest=sha256:570126a086a99dd4d41b01b40abd32f4a79f49d3ddc57379c882ba52b037a094

Observation a42f12ec-f97f-4d9d-9e4c-608520700224 · outbound

This paper cites DiffMOT: A Real-time Diffusion- based Multiple Object Tracker with Non-linear Prediction.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern DiffMOT: A Real-time Diffusion- based Multiple Object Tracker with Non-linear Prediction

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:35:05.026181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:35:02.455903Z digest=sha256:2da39ed330445553b243956c650129b37f964881e0f9b97916914198ab753407

Observation 23ae7859-6b19-43ac-a0f0-317412bd19f1 · outbound

This paper cites YOLOv3: An Incremental Improvement.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern YOLOv3: An Incremental Improvement

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T20:35:02.560025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:35:02.560025Z digest=sha256:395df7d1af47e79b6934f799be47454aa59f5084a18df73e0b72c7410a25fce9

Observation 2b10d502-0483-454f-b0c5-917dca3afbb9 · outbound

This paper cites You Only Look Once: Unified, Real-Time Object Detection.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern You Only Look Once: Unified, Real-Time Object Detection

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:35:04.863491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 709386c8-1f53-4838-8100-4ad2b8e30b6d · outbound

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

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T20:35:02.814256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:35:02.814256Z digest=sha256:851efedd312ecb22c7f72232c26f4005611fa5256f5e64400d02b95ef5063b67

Observation 4b3e6ca0-0273-4f90-bb80-4ee0b9a270c9 · outbound

This paper cites Stanojevic and Branimir T.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern Stanojevic and Branimir T

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:35:04.657175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:35:02.888471Z digest=sha256:13007e7e4f1fb8820775fc76f1912e1b8e2a422d8483dabb9ef1d5b41c63ebe5

Observation af39d86f-c16f-465f-a44b-159e7241f7cc · outbound

This paper cites BoostTrack++: using tracklet information to detect more objects in multiple object tracking, 2024.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern BoostTrack++: using tracklet information to detect more objects in multiple object tracking, 2024

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:35:04.452115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:35:02.972918Z digest=sha256:ffb91e9eafeb406317a415ad0fd308c7f59fbdd8abdcb54b1b2fcdd58934de04

Observation e6ce7cea-c058-4d65-93c6-3cdde975b59d · outbound

This paper cites YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object Detectors.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object Detectors

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:35:04.278543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:35:03.084755Z digest=sha256:87335b40fb1618bb6efcb966def1b9284fb179f7a2dc269ccf32b5a7ed0fee99

Observation 62d97170-9844-4476-81a1-e4338bc28213 · outbound

This paper cites YOLOv9: Learning What You Want to Learn Using Pro- grammable Gradient Information.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern YOLOv9: Learning What You Want to Learn Using Pro- grammable Gradient Information

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:35:04.072226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:35:03.179375Z digest=sha256:cdd40381d5ca4490ff288d95fe8c5bc7a02ebb0bfbadf8e30e309ed62410379f

Observation 7e9f7b8b-de05-40e9-a4ba-cbf6ab1f637a · outbound

This paper cites Simple online and realtime tracking with a deep association metric.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern Simple online and realtime tracking with a deep association metric

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:35:03.856728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:35:03.316189Z digest=sha256:2808a86d709921efd1f7d8ab94b6f8c1b616c050f609bd3ff7ade2dce907ec81

Observation 34bab7c7-aa41-4f36-b6ce-fb0be9c731ae · outbound

This paper cites ByteTrack: Multi-object Tracking by Associating Ev- ery Detection Box.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern ByteTrack: Multi-object Tracking by Associating Ev- ery Detection Box

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:35:03.659947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T20:35:03.430803Z digest=sha256:6f46dd72777237da580f6b03cb21473f677db725f0f816bc76308f0d7aba49b5

Observation 05d0a03f-05f7-48ea-a55a-b591bddaf0b8 · outbound

This paper cites BoT-SORT: Robust Associations Multi-Pedestrian Tracking.

A Novel Tuning Method for Real-time Multiple-Object Tracking Utilizing Thermal Sensor with Complexity Motion Pattern BoT-SORT: Robust Associations Multi-Pedestrian Tracking

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-06T20:35:00.758648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:35:00.758648Z digest=sha256:9351da2658bcf3037d61142c7c82c99db0343cb51d2502ad4ac4736c0405efb1

Pith citing papers

No inbound Pith citation observations are available.