Research on Multi-Object Classification and Recognition 
Methods for Intelligent Vehicles Based on Deep Learning

Ling Wu; Qiong Wu

doi:10.18686/frim.v2i6.4686

Research on Multi-Object Classification and Recognition Methods for Intelligent Vehicles Based on Deep Learning

Ling Wu, Qiong Wu

Abstract

With the development of intelligent transportation systems, multi-object classification and recognition for intelligent vehicles have
become a key research direction in the fields of autonomous driving and intelligent transportation. Deep learning-based methods have become
the mainstream approach to solving this problem. This paper reviews the deep learning-based multi-object classification and recognition techniques, analyzes the advantages and disadvantages of current mainstream methods, and discusses future research directions.

Keywords

Deep learning; Intelligent vehicles; Multi-object classification; Autonomous driving; Convolutional neural networks

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References

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[2] Wu, Chen. Multi-Target Vehicle Detection and Tracking Methods Based on Deep Learning [J]. Practical Automotive Technology, 2023,

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[3] Feng, Jihao. Research on DCT Vehicle Intelligent Control Considering Driving Behavior and Driving Environment [D]. Chongqing

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DOI: http://dx.doi.org/10.18686/frim.v2i6.4686

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