Application of Convolutional Neural Network in Image Recognition

Kaijie Lai

doi:10.62051/ijcsit.v4n1.28

Authors

Kaijie Lai

DOI:

https://doi.org/10.62051/ijcsit.v4n1.28

Keywords:

Image recognition, Convolutional neural network, CNN model, Deep learning, Practical application

Abstract

Image recognition is of great significance for both human social development and daily life. This paper mainly discusses the application research of convolutional neural network (CNN) in the field of image recognition. Firstly, the basic structure and working principle of CNN, including the core components of convolution layer, pooling layer and full connection layer, are introduced, and then the structure and characteristics of the middle layer are explained. Then, this paper compares the advantages and disadvantages of different CNN models such as LeNet-5, AlexNet, GoogLeNet, ResNet, etc., and analyzes their application in face recognition, medical image recognition, traffic recognition, character recognition and other fields. Finally, this paper summarizes the application of CNN in image recognition, and points out the problems faced in its practical application, such as model complexity, computational resource requirements, etc., aiming to provide reference for further research of image recognition technology.

Downloads

Download data is not yet available.

References

[1] Luo Fugui, Song Qian, Qin Yunchu, and so on. Research on the Application of Convolutional Neural Network in Image Recognition [J]. Computers and Information Technology, 2024,32 (3): 51-54. DOI:10.3969/j.issn.1005-1228.2024.03.014.

[2] Nie Jianzheng. Research on transfer learning algorithm based on Convolutional Neural Network and its application in Fine-grained Image Recognition [D]. Shaanxi: Xidian University, 2018. DOI:10.7666/d.D01663960.

[3] Wang Long. Research on semantic segmentation algorithm based on convolutional neural network and its application in image recognition of sweet pepper [D]. Jiangsu: Jiangsu University, 2021.

[4] Chen Beibei. Application of Convolutional Neural Network in Remote Remote Image Recognition [D]. Hebei University of Geosciences, 2018.

[5] Gai Rongli, CAI Jianrong, Wang Shiyu, et al. Review of the application of convolutional neural networks in image recognition [J]. Small Microcomputer System, 2021, 42 (9): 1980-1984. DOI:10.3969/j.issn.1000-1220.2021.09.030.

[6] Time rise. Application of Convolutional neural network in traffic image recognition [D]. Gansu Province: Northwest Normal University, 2021.

[7] Conshoman. Research and Application of Image Recognition Method Based on Convolutional Neural Network [D]. Hebei: Yanshan University, 2021.

[8] Li Xiaoyang, Xie Hengyi, Han Zhenhui, et al. Research on the Application of Convolutional Neural Network in Image Recognition Technology [J]. Energy and Environmental Protection, 2020, 42 (6): 73-76.

[9] Wang Xinyu. Application of convolutional neural network in finger vein recognition [D]. Sichuan: Southwest University of Science and Technology, 2022.

[10] Liu Bingzai. Research on Chinese Verification code identification technology based on Convolutional Neural Network [D]. Wuhan University of Light Industry, 2023.