The Analysis of Network Course in Intelligent Image Acquisition Education System Based on Deep Learning

The Internet, big data, and intelligent robots have transformed online education. This study introduces an Enhanced Convolutional Neural Network (CNN+) model optimized with refined weight initialization and strategic activation functions for image recognition. The CNN+ model achieves 99.5% accuracy on MNIST and 75.2% on CIFAR-10, with the Sigmoid-ReLU hybrid boosting performance to 99.2% and 72.3% respectively. These optimizations underscore the importance of strategic CNN architecture choices in enhancing performance, supporting advancements in online education platforms. The CNN+ model represents a significant breakthrough in image recognition for online education.