Application and Design Implementation of Deep Learning Algorithms Based on Artificial Intelligence in Virtual Reality Interaction

In recent years, the rapid advancement of virtual reality (VR) technology has greatly enhanced user interaction experiences. Concurrently, artificial intelligence (AI), particularly deep learning algorithms, have shown powerful potential in areas such as gesture recognition, offering new perspectives and methodologies for VR interaction design. This article begins by introducing the fundamental theory of deep learning, encompassing convolutional neural networks (CNN), nonlinear activation functions, loss functions, and the training process. Subsequently, it delves into the application of deep learning in gesture recognition, conducting a detailed analysis of data collection and preprocessing for datasets, network model design, and optimization strategies. Following this, the effectiveness and practicality of the proposed methods are validated through a series of experiments. Furthermore, the performance of the model at different testing stages is assessed. Ultimately, the advantages and challenges of deep learning-based gesture recognition in virtual reality interaction are summarized, accompanied by an outlook on future developmental directions.