@inproceedings{e77bfceda3cc4498b747a9e6a52f1746,
title = "Research on Infrared Small Target Detection Algorithm Based on YOLOv5 and Enhanced KCF Algorithm with Kalman Filter",
abstract = "This paper mainly compares and studies three target detection algorithms-YOLOv5, KCF algorithm and the enhanced KCF algorithm with Kalman Filter. The features, advantages and disadvantages of these algorithms are summarized. Also, this paper proposes a combined target detection algorithm that uses YOLOv5 to identify the target in the first frame and enhanced KCF algorithm with Kalman Filter to track the target in the following frames. The proposed algorithm is tested and validated on an open-source infrared small target dataset. The results show that the proposed algorithm can achieve a high recognition rate without consuming too many computational resources, and it is especially robust compared to pure KCF algorithm when dealing with jerky videos.",
keywords = "IRST, KCF, Kalman Filter, Targat Detection Algorithm, YOLOv5",
author = "Zhihao Gu and Hengyi Peng and Bo Wei and Chunling Yang",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 5th IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2023 ; Conference date: 14-07-2023 Through 16-07-2023",
year = "2023",
doi = "10.1109/ICPICS58376.2023.10235496",
language = "英语",
series = "2023 IEEE 5th International Conference on Power, Intelligent Computing and Systems, ICPICS 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "417--422",
booktitle = "2023 IEEE 5th International Conference on Power, Intelligent Computing and Systems, ICPICS 2023",
address = "美国",
}