Face detection and recognition technology based on EfficientNet and BNNeck

Runjia Li
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Abstract

Face detection is the premise of face attribute recognition, and face attribute recognition is the deep understanding of the computer to face image features. In the construction and development of modern society, with the continuous development of computer vision technology, identity recognition technology with biometric recognition as the core has been paid attention to, and began to be widely used in face verification, interpersonal interaction, precision delivery and other fields. Therefore, on the basis of understanding the current research status of artificial intelligence technology theory and EfficientNet, BNNeck algorithm design, the paper deeply discusses the neural network as the core of the cascade face detection and recognition technology in the new era. The final results show that the improved cascaded face recognition method proposed in this paper has research value.
基于EfficientNet和BNNeck的人脸检测与识别技术
人脸检测是人脸属性识别的前提,而人脸属性识别是计算机对人脸图像特征的深入理解。在现代社会的建设和发展中,随着计算机视觉技术的不断发展,以生物特征识别为核心的身份识别技术受到了重视,并开始广泛应用于人脸验证、人际互动、精准投放等领域。因此,本文在了解人工智能技术理论和effentnet、BNNeck算法设计研究现状的基础上,深入探讨了以神经网络为核心的新时代级联人脸检测识别技术。最终结果表明,本文提出的改进级联人脸识别方法具有研究价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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