Optimization study of convolutional neural network model based on computer simulation context
Xuxu Zhang, Jikai Hua · 2023
Convolutional Neural Network (CNN) is the most successful mathematical model of an artificial neural network used in the fields of computer vision, image recognition, and classification. High-performance neural network structures are large in size, and a large number of multiplicative-additive calculations are required for a complete inference process. Training out a high-performance convolutional neural network model requires tens of times more computation than the inference process. The current theoretical and technical level cannot achieve a model that can be universally applied to all domains, and different application scenarios require designing specific neural network structures and collecting specific data sets. Large computing power requirements and high-quality data acquisition are two key components for training to obtain high-performance convolutional neural networks.