Mr. Qi Han Profile

Qi Han

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Proceedings Article | 30 April 2024 Paper

The survey of one-stage anchor-free real-time object detection algorithms

Peng He, Weidong Chen, Lan Pang, Weiguo Zhang, Yitian Wang, Weidong Huang, Qi Han, Xiaofeng Xu, Yuan Qi

Proceedings Volume 13156, 1315602 (2024) https://doi.org/10.1117/12.3012931

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With the improvement of computer computing power, the object detection algorithms based on deep neural network has ushered in vigorous development, and has been widely used in industry, agriculture, medicine, military and other fields. One-stage object detection algorithms shows the superiority in real-time detection compared to other object detection algorithms such as two-stage object detectors or ViT-based detectors. At the same time, more and more anchor-free detectors show the advanced nature of anchor-free algorithms compared to anchor-based detectors. In this paper, we review the one-stage anchor-free real-time object detection algorithms in recent years, and analyze the application scenarios and optimization strategies of future object detection algorithms. Firstly, the principle and advantages of anchor-free object detection algorithms and one-stage object detection algorithm are introduced. Secondly, the network structure and innovation of anchor-free object detection algorithms in recent years are summarized. Finally, the possible development direction and trend of one-stage anchor-free real-time object detection algorithms in the future are proposed.

Proceedings Article | 25 January 2024 Paper

Improvement of target recognition ability based on micro-scanning

Bingtao Guo, Wenbo Duan, Qi Han, Pengcheng Cai, Yitian Wang, Dong Ren, Hang Yuan

Proceedings Volume 12972, 129720L (2024) https://doi.org/10.1117/12.3022761

KEYWORDS: Target recognition, Target detection, Imaging systems, Sensors, Infrared imaging, Human vision, Correlation coefficients, Statistical methods, Principal component analysis

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Aiming at the requirements of optical detection and recognition for wide-area and continuous monitoring of aircraft targets, the influence of micro-scanning on the imaging and recognition performance of aircraft target is discussed in this article. This paper proposes a statistical method for aircraft target recognition threshold based on human vision. On the basis of analyzing the imaging principle of micro-scanning, the edge feature of the aircraft target is extracted using the Canny algorithm. Then the main axis direction of the aircraft target is determined based on the principal component analysis (PCA). Sampling is performed at equal intervals along the vertical direction of the main axis of the aircraft, and the characteristic parameters of the contour edge of the aircraft target are extracted. The matching algorithm of Spearman rank correlation coefficient is used to judge whether the target is recognizable. Research results show that the influence of sampling phase on target imaging can be eliminated by micro-scanning. The recognition distance of the target is significantly improved with the increase of scanning times. A smaller optical system aperture can be selected to achieve the task of target recognition when the micro-scanning imaging mode is used.

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