Implementation of YOLOv4 Algorithm for Multiple Object Detection in Image and Video Dataset using Deep Learning and Artificial Intelligence for Urban Traffic Video Surveillance Application-Reference-Cited by-同舟云学术

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Implementation of YOLOv4 Algorithm for Multiple Object Detection in Image and Video Dataset using Deep Learning and Artificial Intelligence for Urban Traffic Video Surveillance Application

Published:2021-09-15 Issue: Volume: Page:
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Container-title:2021 Fourth International Conference on Electrical, Computer and Communication Technologies (ICECCT)
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Author:

Naik Umesh Parameshwar,Rajesh Varadi,R Rohith Kumar,Mohana

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9616617/9616621/09616625.pdf?arnumber=9616625

Cited by 9 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Integrating Object Detection and Optical Flow Analysis for Real-time Road Accident Detection;2024 International Symposium on Intelligent Robotics and Systems (ISoIRS);2024-06-14

2. Vision-Based Multi-detection and Tracking of Vehicles Using the Convolutional Neural Network Model YOLO;Lecture Notes in Networks and Systems;2024

3. A supervised approach using transformer networks for the detection of turning-related anomalies in urban intersections;2023 13th International Conference on Computer and Knowledge Engineering (ICCKE);2023-11-01

4. A Survey of Video Surveillance Systems in Smart City;Electronics;2023-08-23

5. Detection of Moving Object Using Modified Fuzzy C-Means Clustering from the Complex and Non-stationary Background Scenes;Springer Proceedings in Mathematics & Statistics;2023

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