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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 8 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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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=sha256:45e730b5b2249f29ecbba5eb19b38f4bd044c71102e295df4ea70cb6bcba1eb7

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T20:35:01.488887Z digest=sha256:eafd2d43a8f56e9b5a7b617575d64f0252e2f09560ea239b6685eb95db799c57

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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T20:35:01.825259Z digest=sha256:51dadb42a5ffd7dda5282681f6d2bdadde85b015a4b376c0c44af6165d37cb81

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

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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=sha256:72df3a576d8811ad515e74d3c7f50cc52f904b223476c71487a85c0a3f6ea628

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T20:35:02.245603Z digest=sha256:9d6279fc185da6fd19a3bf2796d8830768e515068e7815743c64137dfb61bbd1

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 2026-08-08T06:32:00.761636+00:00.

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T20:35:02.455903Z digest=sha256:68347fea67f90ff0b1617c9c6d4fb5fe1c828e454cb41e29f01023c99efc19ec

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.

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T20:35:02.698281Z digest=sha256:8e2eee844b90fec081641ddbf44ebe5ae82c64d0bca2ef95286ee281bbf3258c

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=sha256:08df6433b537854f5761bb543bb55d533927d77a4877421a1fca448c3eb67047

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 2026-08-08T06:32:00.761636+00:00.

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T20:35:02.972918Z digest=sha256:fc2a78c220ebd1b439381bf6409a1fdb74cac573dffd84dadc87e66308fe9821

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T20:35:03.084755Z digest=sha256:82e0f422f5a43796e2c8c5f4094bc5f2494569f1c066cc94a6fb2c34e9df7545

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T20:35:03.179375Z digest=sha256:dc2453bd3ee6974090c6ceec675d3f00b9360ddc063fb1808053fdb7575a31f6

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T20:35:03.316189Z digest=sha256:8ee6304bf6489e2e5ff34584139bbfc2560800701c49108fca20b4fa19cde9b8

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T20:35:03.430803Z digest=sha256:9a06eced95572707f44def408f7cdb527b38b2ca9a6bea2f113884e5a6714613

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:cd38982b6f9698fc6895a0b76725653b206127b87ea37ff4d231cfae4d56bf90

Pith citing papers

No inbound Pith citation observations are available.