AI Face Recognition and Processing Technology Based on GPU Computing
DOI:
https://doi.org/10.53469/jtpes.2024.04(05).02Keywords:
Real-time object detection, Face recognition, GPU acceleration, TensorRTAbstract
In recent years, with the development of deep neural network technology, real-time object detection has become increasingly common in mobile applications. However, practical application requirements drive the algorithm to optimize in terms of speed, energy consumption and accuracy. This paper introduces the application of artificial intelligence in the field of face recognition, especially using TensorRT accelerated reasoning technology to improve the speed and performance of face recognition. At the same time, the paper also discusses the key role of GPU computing in face recognition, and expounds the importance of AI chips for optimizing inference tasks. Through the analysis of experimental results and methods, the performance advantages and application prospects of BlazeFace algorithm in mobile applications are demonstrated, which provides a valuable reference for industry.
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Copyright (c) 2024 Huixiang Li, Ang Li, Yuning Liu, Yiyu Lin, Yadong Shi
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
