Mr. JiangYong Li Profile

JiangYong Li

at North China Institute of Optoelectronic Technology

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Author

Publications (6)

Proceedings Article | 12 April 2023 Paper

Research on dual-band infrared passive ranging algorithm by airborne remote single station

Xiaopei Huo, Miaoyan Wang, Jiangyong Li, Songlin Yu

Proceedings Volume 12565, 125651Y (2023) https://doi.org/10.1117/12.2662539

KEYWORDS: Atmospheric modeling, Ranging, Infrared radiation, Target detection, Medium wave, Infrared imaging

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Proceedings Article | 23 January 2023 Paper

Airborne infrared small target recognition algorithm based on improved efficientdet

Jiale Song, Tong Liu, Dezhen Yang, Jiangyong Li

Proceedings Volume 12557, 1255719 (2023) https://doi.org/10.1117/12.2651526

KEYWORDS: Detection and tracking algorithms, Infrared radiation, Target recognition, Infrared imaging, Target detection

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Proceedings Article | 20 January 2023 Paper

Multi-angle infrared vehicle target recognition based on light-head R-CNN

Tong Liu, Dezhen Yang, Jiale Song, Jiangyong Li

Proceedings Volume 12555, 125550C (2023) https://doi.org/10.1117/12.2651537

KEYWORDS: Target recognition, Detection and tracking algorithms, Infrared radiation, Infrared imaging, Convolution, Image processing, Feature extraction

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There are deviations in the images of the same target at different angles, so the multi-angle infrared images contain additional classification and identification feature information. Therefore, the multi-angle image acquisition system can effectively solve the problems such as occlusion and small target size that cannot be recognized with high precision. Combined with the multi-angle acquisition system, a multi-angle infrared vehicle target recognition algorithm based on Light-Head R-CNN was proposed. Firstly, inputted the multi-angle infrared images of the same target into the ConvNeXt backbone network for feature extraction; Secondly, in order to reduce the amount of model parameters and realize the lightweight of the network, the traditional convolution in the backbone network was replaced with Ghost Module, which reduced the amount of FLOPs and parameters by about 50%; At the same time, according to the characteristics of infrared vehicle targets, the Light-Head R-CNN target recognition algorithm was improved, and an ultra-lightweight ECA module without dimensionality reduction local cross-channel interaction was added to improve the performance of the network for infrared vehicle target recognition; Finally, the Dempster synthesis rule was used to perform data fusion on the recognition accuracy of images from different angles predicted by the network to obtain the final recognition accuracy. It had been verified that compared with single-angle images, when the number of input angles was 2, the recognition accuracy of the algorithm in the constructed data set was improved by 3.8%; The recognition accuracy reached 90.1%, it was optimal, while the input infrared images were distributed at a certain angle and the number was 5, at the same time the speed achieved 44fps. The results fully demonstrated the feasibility of the proposed algorithm in improving the recognition accuracy, and provided a theoretical and experimental basis for enhancing the performance of the target recognition algorithm.

Proceedings Article | 15 February 2022 Paper

Overview on infrared dim target tracking

Yun-Peng Bai, De-Zhen Yang, Song-Lin Yu, Jiang-Yong Li, Cheng-Zhang Huang

Proceedings Volume 12166, 1216678 (2022) https://doi.org/10.1117/12.2617932

KEYWORDS: Infrared radiation, Detection and tracking algorithms, Image filtering, Infrared search and track, Electronic filtering, Infrared imaging, Particles, Particle filters, Optical filters, Evolutionary algorithms

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Proceedings Article | 15 February 2022 Paper

Infrared dim target detection technology based on IRI-CNN

Jia-Kai He, De-Zhen Yang, Cheng-Bin An, Jiang-Yong Li, Cheng-Zhang Huang

Proceedings Volume 12166, 121665E (2022) https://doi.org/10.1117/12.2617526

KEYWORDS: Target detection, Detection and tracking algorithms, Infrared detectors, Neural networks, Image enhancement, Infrared imaging, Submerged target detection

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Proceedings Article | 15 February 2022 Paper

Research on infrared target recognition algorithm based on SSD-MobileNetv1 network

Siyuan Cheng, Dezhen Yang, Jiangyong Li, Peng Jia

Proceedings Volume 12166, 121666J (2022) https://doi.org/10.1117/12.2617798

KEYWORDS: Target recognition, Infrared radiation, Data modeling, Infrared imaging, Target detection, Convolution, Thermal modeling, Performance modeling, Image enhancement, Electro optical modeling

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Showing 5 of 6 publications

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