Research on obstacle recognition technology based on optimized deep learning algorithm

Wen Zhou; Hanyu Meng; Ainan Huang; Xinxin Sun; Shizhou Yao

doi:10.1117/12.2678882

25 May 2023 Research on obstacle recognition technology based on optimized deep learning algorithm

Wen Zhou, Hanyu Meng, Ainan Huang, Xinxin Sun, Shizhou Yao

Proceedings Volume 12712, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023); 127121B (2023) https://doi.org/10.1117/12.2678882
Event: International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023), 2023, Huzhou, China

Abstract

Several machine learning algorithms for image processing and computer vision applications have been proposed in the past decade. LBP, HAAR are some popular algorithms that are widely used in face recognition and produce excellent results. However, most of these algorithms are not suitable for real-time recognition in unconstrained environments. Recently, the most advanced deep learning technology has become the new favorite of traditional machine learning algorithms. In this paper, the obstacle recognition technology based on optimized deep learning algorithm, based on the traditional GS optimization algorithm, the gray wolf optimization algorithm is used to optimize the image features .Firstly, this paper creates an obstacle image database to provide deep learning data. Create cnn model in MATLAB to learn the features of pictures in the database and identify the categories of pictures.

Citation Download Citation

Wen Zhou, Hanyu Meng, Ainan Huang, Xinxin Sun, and Shizhou Yao "Research on obstacle recognition technology based on optimized deep learning algorithm", Proc. SPIE 12712, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023), 127121B (25 May 2023); https://doi.org/10.1117/12.2678882

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