1. Image recognition based on lightweight convolutional neural network: Recent advances.
- Author
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Liu, Ying, Xue, Jiahao, Li, Daxiang, Zhang, Weidong, Chiew, Tuan Kiang, and Xu, Zhijie
- Subjects
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CONVOLUTIONAL neural networks , *DEEP learning , *IMAGE recognition (Computer vision) , *COMPUTER vision - Abstract
Image recognition is an important task in computer vision with broad applications. In recent years, with the advent of deep learning, lightweight convolutional neural network (CNN) has brought new opportunities for image recognition, which allows high-performance recognition algorithms to run on resource-constrained devices with strong representation and generalization capabilities. This paper first presents an overview of several classical lightweight CNN models. Then, a comprehensive review is provided on recent image recognition techniques using lightweight CNN. According to the strategies applied to optimize image recognition performance, existing methods are classified into three categories: (1) model compression, (2) optimization of lightweight network, and (3) combining Transformer with lightweight network. In addition, some representative methods are tested on three commonly used datasets for performance comparison. Finally, technical challenges and future research trends in this field are discussed. • A comprehensive review of recent advances in lightweight CNN for image recognition. • Classification according to different optimization directions. • Present the evaluation results of different representative lightweight CNN methods. • Discuss future research trends of image recognition. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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