Prof. Yapeng Wang Profile

Prof. Yapeng Wang

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Proceedings Article | 24 October 2024 Paper

Research and application based on the improved YOLO V7 target detection algorithm

Tenghui Wang, Xiaofeng Zhang, Yan Ma, Yapeng Wang, Haijun Xie, Mingchao Zhu, Binghua Su, Dong Yao

Proceedings Volume 13396, 1339610 (2024) https://doi.org/10.1117/12.3050416

KEYWORDS: Detection and tracking algorithms, Object detection, Target detection, Feature extraction, Mathematical optimization

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At present, YOLO-based of algorithms have been widely used in urban planning, traffic monitoring, ecological protection, military security and other fields, and their applicable scenarios are expanding. In view of the problems of high misdetection rate, high omission rate and insufficient accuracy in the image target detection task, this topic is dedicated to study the improved target detection algorithm based on YOLO V7. In order to optimize the time cost and computing resource consumption, the Anchor-free based design is introduced, and through optimizing the design of decoupling head, the independent processing of classification and regression tasks is realized to improve the efficiency of feature extraction. Based on this method, the CBATM attention mechanism is used to better capture the intercorrelations between features and improve the representational ability of the model. In the loss function section, this paper adopts the SimOTA method in YOLOX to realize the dynamic number allocation of positive samples, which greatly reduces the training time. Improved YOLO V7 target detection algorithm in the PASCAL VOC challenge public dataset VOC2007 data set, the results show that the improved YOLO V7 target detection algorithm than the original YOLO V7, has higher detection accuracy and efficient performance, the average detection accuracy (mAP) increased by 2.27%, compared with other classic target detection algorithm, the improved YOLO V7 performance is more accurate and efficient.

Proceedings Article | 15 December 2023 Paper

Research on underwater image enhancement algorithm based on physical model

Tenghui Wang, En Zhang, Yan Ma, Yapeng Wang, Yunting Lai, Zhenbo Wang, Zizhao Yuan, Chun Yang

Proceedings Volume 12971, 129710W (2023) https://doi.org/10.1117/12.3017410

KEYWORDS: Image enhancement, Image processing, Underwater imaging, Cameras, Signal attenuation, Image quality, Particles, Tunable filters, Image transmission, Deblurring

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In this research work, an improved underwater image enhancement algorithm is presented that is based on physical modeling techniques. It aims to improve the quality of underwater images by addressing color differences and blur. The proposed algorithm performs better than other advanced and classical underwater image enhancement methods. The method is composed of a two-step process. First, a coarse transfer map is estimated, which optimizes the contrast and minimizes the loss of information during the image mapping process. Dark channel preprocessing and guided filter refinement are used to improve transmission map accuracy. Second, the occluded light is estimated by considering the differential attenuation of the red, green, and blue light underwater, thereby mitigating the color differences caused by the attenuation effects and solving the blur problem based on the image models. In addition, the gray world method is used for color correction, resulting in a deblurred and color corrected underwater image. In particular, it addresses color differences and blurriness in underwater imagery caused by light attenuation at different wavelengths, visible light diffusion, and diffusion from plankton and debris. The ability to significantly improve the quality of underwater images is the significance of this enhanced algorithm. This enhancement gives researchers a more apparent and reliable basis for understanding and analyzing underwater environments and phenomena. It has far-reaching implications for various fields, including marine biology, underwater archaeology, and oceanography, as it improves the accuracy of research and applications in these domains.

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