卷积神经网络
计算机科学
人工智能
深度学习
领域(数学)
过程(计算)
人工神经网络
新认知
一般化
模式识别(心理学)
时滞神经网络
机器学习
数学
操作系统
数学分析
纯数学
作者
Zhenzhu Guo,Yiduo Zhang
标识
DOI:10.1109/scset55041.2022.00059
摘要
Convolutional neural networks have powerful generalization and expression capabilities for extracting deep-level features of images. Their emergence has further promoted the development of artificial intelligence, and greatly improved the image recognition and detection effects and computer operating speed. With the advent of the global intelligent era, image recognition and detection technology based on convolutional neural networks has emerged in various fields of workpiece detection, and it has also brought challenges for professionals in this field to optimize intelligent algorithms. In this paper, the recognition process of the convolutional neural network and the current research status of the convolutional neural network in the recognition of bolt looseness images are described and prospected.
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