深度学习模型中间层特征压缩技术综述.

As a new research hotspot in deep learning, intermediate deep feature compression has gotten a great deal of attention and has been applied to edge-cloud intelligent collaboration. This paper summarized the current state of research on the intermediate deep feature compression and analyzed the problems in the current methods. Firstly, it introduced three kinds of intermediate deep feature compression from aspects of image/video coding framework, channel bit allocation and network units. Then it did the comparisons of the data set performance between the three intermediate deep feature compression. Finally, this paper discussed the existing challenges and solutions in intermediate deep feature compression and looked forward to the feature trends of intermediate deep feature compression. [ABSTRACT FROM AUTHOR]