Deep learning is a new research area in machine learning. Currently

extracting features by deep learning for visual object recognition and behavior recognition capture many attentions. To draw more attention from research community about deep learning

and to push forward the research frontier of object and behavior recognition

we give a general progress overview for deep learning and its application to visual object and behavior recognition. First

we give a general introduction to deep learning

including the basic situation

main concepts and principle. Then

some new progresses on using deep learning in visual object recognition and behavior recognition are presented. A discussion about the differences between deep learning and neural network as well as the advantage and disadvantage of deep learning are given

the main existing problems that should be solved for deep learning theory are pointed. This paper should provide some help for the research community on applying the deep learning to the visual object and behavior recognition.