Summary of Target Detection Algorithms

• Published in: Journal of physics. Conference series Vol. 1757; no. 1; pp. 12003 - 12013
• Main Authors: Li, Wei, Feng, Xiang Sheng, Zha, Kaiwen, Li, Shuning, Zhu, Hua Sheng
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.01.2021
• Subjects: Algorithms; Anchor bolts; Computer vision; Convolutional Neural Network; Model accuracy; Physics; Target Detection
• ISSN: 1742-6588; 1742-6596
• DOI: 10.1088/1742-6596/1757/1/012003

In recent years, the soaring development of CNN has facilitated the maturity of the Computer Vision Algorithm. This paper will briefly introduce some representative Target Detection Algorithm, and systematically analyze the underlying problems, the modified methods, and the prospective direction of the algorithm in accordance with its merits and demerits. It is generally divided into a single-stage detection model and a double-stage detection model in terms of whether candidate areas need to be extracted during target detection for further tasks. Featured with scale in the double-stage detection model, the algorithm is divided into single-scale detection and multi-scale detection based on whether it can appropriately integrate with a network structure, which enhances the accuracy of the network model towards small targets. Meanwhile, it can also be divided into anchor-base and anchor-free in a single-stage detection model on the basis of the anchor bolt. A predictable development of the Target Detection Algorithm will show to us in the future.