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In this study, we explore deep learning models for single-character Chinese character recognition tasks, with a special focus on two architectures: VGG19 and EfficientNetV2. By improving recognition accuracy with limited computational resources and dataset size, this study aims to address real-world challenges.In the field of image recognition, deep learning has shown excellent ability, especially the importance of convolutional Neural Network (CNN). This study reviews the history of handwritten Chinese character recognition and explores the application of deep learning in various fields such as object detection, image classification, and semantic segmentation. The research methodology incorporates problem analysis, data collection, model construction, training, and result generation. PyTorch is used as the basic framework to implement the model, and strict data preprocessing is conducted to optimise the …