Paper Citation Record · LEDGER

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis

As of 18 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2506.16186.

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

pith.paper-citation-record.v1
2506.16186 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:48:48.063160Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

23 of 23 outbound references displayed

verified exact2
verified fuzzy19
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fe5a7290-af18-45b6-a9e5-597c81f21796 · outbound

This paper cites Review of accident detection methods using dashcam videos for autonomous driving vehicles,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis Review of accident detection methods using dashcam videos for autonomous driving vehicles,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:52.891865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3213daef-2bce-4a9c-80e2-82d2293af26c · outbound

This paper cites TP-YOLOv8: A lightweight and accurate model for traffic accident recognition,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis TP-YOLOv8: A lightweight and accurate model for traffic accident recognition,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:52.647998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a216b464-3b65-42e6-89ad-fc33bb7e7700 · outbound

This paper cites Smart city transportation: Deep learning ensemble approach for traffic accident detection,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis Smart city transportation: Deep learning ensemble approach for traffic accident detection,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T23:48:45.881441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32fdd834-3b3c-4f5e-8a3c-511e3df2234a · outbound

This paper cites Generative adversarial networks (GANs) for image augmentation in agriculture: A sys- tematic review,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis Generative adversarial networks (GANs) for image augmentation in agriculture: A sys- tematic review,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:52.407226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0487b26e-ee8a-4608-8bcf-937ddcdcf84a · outbound

This paper cites Recent Advances in Traffic Accident Analysis and Prediction: A Comprehensive Review of Machine Learning Techniques.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis Recent Advances in Traffic Accident Analysis and Prediction: A Comprehensive Review of Machine Learning Techniques

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-06T23:48:48.780780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 536560f2-3db6-46df-9643-e939c9076621 · outbound

This paper cites DMDAT: Diffusion model- based data augmentation technique for vision-based accident detection in vehicular networks,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis DMDAT: Diffusion model- based data augmentation technique for vision-based accident detection in vehicular networks,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:52.232901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f65074f9-75a4-4d07-bc86-19f0105b386f · outbound

This paper cites STAN: Synthetic network traffic generation with generative neural models,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis STAN: Synthetic network traffic generation with generative neural models,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:52.080819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4ccaf40e-4c54-40a3-bf0e-ab0b07b3ecef · outbound

This paper cites Anomaly detection in road traffic using visual surveillance: A survey,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis Anomaly detection in road traffic using visual surveillance: A survey,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:51.928213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f3bce852-a1b4-4d29-b1ef-85e95ae4c222 · outbound

This paper cites an unresolved cited work.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-06T23:48:51.714014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0ff743eb-9a81-46e6-9706-c4776a187d03 · outbound

This paper cites AI driven anomaly detection in network traffic using hybrid CNN-GAN,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis AI driven anomaly detection in network traffic using hybrid CNN-GAN,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:51.527890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 50b9f496-073f-45b6-8560-57e8d1d87360 · outbound

This paper cites Developing future human-centered smart cities: Critical analysis of smart city security, data management, and ethical challenges,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis Developing future human-centered smart cities: Critical analysis of smart city security, data management, and ethical challenges,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:51.359109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 891abbb3-41be-4575-972d-fd7fdbe9d8ef · outbound

This paper cites Advancements In Crowd-Monitoring System: A Comprehensive Analysis of Systematic Approaches and Automation Algorithms: State-of-The-Art.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis Advancements In Crowd-Monitoring System: A Comprehensive Analysis of Systematic Approaches and Automation Algorithms: State-of-The-Art

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-06T23:48:48.467181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0dc2a86b-894e-43f1-92ed-8ce84ab1b5bb · outbound

This paper cites Review of on-scene management of mass-casualty attacks,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis Review of on-scene management of mass-casualty attacks,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:51.137732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation eef4313f-b8be-477d-9197-76ce0823ede4 · outbound

This paper cites Intelligent algo- rithms for incident detection and management in smart transportation systems,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis Intelligent algo- rithms for incident detection and management in smart transportation systems,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:50.986170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 90a82e3b-de06-42f7-bcdb-50fb7332f6fb · outbound

This paper cites Future smart cities: Requirements, emerging tech- nologies, applications, challenges, and future aspects,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis Future smart cities: Requirements, emerging tech- nologies, applications, challenges, and future aspects,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:50.822467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 950df0c5-49d0-4fc4-83ca-38f29954197e · outbound

This paper cites A GAN-augmented CNN approach for automated roadside safety assessment of rural roadways,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis A GAN-augmented CNN approach for automated roadside safety assessment of rural roadways,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:50.682260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cae99182-2270-4e42-a345-cca0b948cdd6 · outbound

This paper cites Generative adversarial networks (GAN) and HDFS-based realtime traffic forecasting system using CCTV surveillance,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis Generative adversarial networks (GAN) and HDFS-based realtime traffic forecasting system using CCTV surveillance,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:50.413130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dbae4da4-8dfb-419d-ade2-b54dbfa25be3 · outbound

This paper cites Anomaly detection in traffic surveillance videos with GAN-based future frame prediction,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis Anomaly detection in traffic surveillance videos with GAN-based future frame prediction,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:50.131270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 46e8dd89-2c12-4860-9433-4fcfd39ddb94 · outbound

This paper cites Real- time event-driven road traffic monitoring system using CCTV video analytics,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis Real- time event-driven road traffic monitoring system using CCTV video analytics,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:49.862945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation acfc4cdb-5f1b-4100-a6f8-63684f01d538 · outbound

This paper cites Normalized attention neural network with adaptive feature recalibration for detecting the unusual activities using video surveillance camera,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis Normalized attention neural network with adaptive feature recalibration for detecting the unusual activities using video surveillance camera,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:49.722406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0d3f79f5-81c9-4d54-8d9a-12950d8495a0 · outbound

This paper cites From detection to action: A multimodal AI framework for traffic incident response,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis From detection to action: A multimodal AI framework for traffic incident response,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:49.503176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7c39db2b-2ca4-4003-9711-ac0fc6eba12b · outbound

This paper cites A deep autoencoder-based approach for suspicious action recognition in surveillance videos,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis A deep autoencoder-based approach for suspicious action recognition in surveillance videos,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:49.293073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9463e804-bf02-49d2-993a-89aaa3bf6a41 · outbound

This paper cites A comprehensive analysis of real-time video anomaly detection meth- ods for human and vehicular movement,.

Integrating Generative Adversarial Networks and Convolutional Neural Networks for Enhanced Traffic Accidents Detection and Analysis A comprehensive analysis of real-time video anomaly detection meth- ods for human and vehicular movement,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:48:49.040456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

No inbound Pith citation observations are available.