深度学习是机器学习中的一个新的研究领域。通过深度学习的方法构建深度网络来抽取特征是目

前目标和行为识别中得到关注的研究方向。为引起更多计算机视觉领域研究者对深度学习进行探索和讨论，并推

动目标和行为识别的研究，对深度学习及其在目标和行为识别中的新进展给予概述。方法首先介绍深度学习领

域研究的基本状况、主要概念和原理 然后介绍近期利用深度学习在目标和行为识别应用中的一些新进展。结

果阐述了深度学习与神经网络之间的关系，深度学习的优缺点，以及目前深度学习理论需要解决的主要问题。

结论该文对拟将深度学习应用于目标和行为识别的研究人员有所帮助。-Depth learning machine learning is a new field of research. To extract features to build depth by deep learning of the network is to head

Before the objectives and behavior recognition obtained in research attention. Computer vision is to attract more researchers to explore the depth of study and discussion, and push

Moving targets and conduct research to identify the depth of learning and new progress in the goals and behavior recognition to give an overview. The method first introduced collar depth study

Basic Situation field research, the main concepts and principles　then describes recent advances in deep learning some new goals and behavior recognition applications use. Knot

Fruit describes the relationship between the depth of learning and neural networks, the advantages and disadvantages of deep learning and deep learning theory main problems to be solved.

Conclusion In this paper intends to apply to the target depth of learning and behavior recognition researchers help.