Abstract: This paper firstly introduces the development of Deep Belief Network （DBN） based on theory foundation. Afterwards, the difference between deep network structure and shallow network structure is analyzed. Finally, the literature makes a study and analysis of DBN, in the field of text detection, facial and expression recognition, and remote sensing image classification by quoting multiple representative documents. Through a comprehensive introduction to the deep learning model DBN and deeply understanding the construction and practical application of DBN, it provides researchers with the idea of improving DBN and applying it to a wider emerging field in the future.

Key words: Deep Belief Network（DBN）, text detection, facial and expression recognition, remote sensing image field

摘要： 介绍深度置信网络（DBN）理论基础的发展，对比分析深层结构DBN与浅层网络结构的差异，最后引用多篇文献分析研究DBN在文字检测、人脸及表情识别领域和遥感图像领域的应用效果。全面介绍了深度学习模型DBN，深入分析DBN的构建与实际应用，为研究人员提供改进DBN的思路，以期在未来将其运用到更宽广的新兴领域中。

关键词: 深度置信网络, 文字检测, 人脸及表情识别, 遥感图像领域