Binary Image Classification with ResNet

The paper discusses the approach to binary image classification with ResNet based deep learning. Its actuality is the automatic image classification process and subject-the use of the methods of data augmentation and in the improvement of the model accuracy-deep neural networks. The goal of this research was to develop and assess the efficiency of using the pre-trained ResNet network for solving the binary classification problem. Such image preprocessing and implementation for the augmentation method and mixed learning were conducted to optimize the classification process. The experimental results discussed point towards integration in preprocessing methods, dynamic image loading, and computational process optimization that drive substantial growth in the quality of classification, which carries great practical value in further explorations in this area