基于深度学习的视觉感知技术在图像通信系统中的应用

Application of Visual Perception Technology Based on Deep Learning in Image Communication System

深度学习作为现代人工智能的核心技术,近年来在视觉感知领域取得了显著突破。得益于其强大的非线性表达能力和自适应特征学习机制,深度学习模型能够有效捕捉图像数据的复杂结构和隐含规律,从而在图像处理任务上展现出超越传统方法的性能。鉴于深度学习在解决图像通信系统现存问题上的巨大潜力,文章旨在深入探讨基于深度学习的视觉感知技术在图像通信系统中的理论基础和具体应用,以期为深度学习在图像通信领域的理论研究与实践应用提供参考。

As the core technology of modern artificial intelligence,deep learning has made remarkable breakthroughs in the field of visual perception in recent years.Thanks to its powerful nonlinear representation ability and adaptive feature learning mechanism,deep learning models can effectively capture the complex structure and hidden laws of image data,thus showing better performance than traditional methods in image processing tasks.In view of the great potential of deep learning in solving existing problems in image communication systems,this paper aims to deeply explore the theoretical basis and specific application of visual perception technology based on deep learning in image communication systems,hoping to provide references for theoretical research and practical application of deep learning in the field of image communication.