Learning Deep CNN Structures
Conference: CNNA 2016 - 15th International Workshop on Cellular Nanoscale Networks and their Applications
08/23/2016 - 08/25/2016 at Dresden, Deutschland
Proceedings: CNNA 2016
Pages: 2Language: englishTyp: PDF
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Authors:
Mueller, Jens; Walz, Simon; Tetzlaff, Ronald (Institute of Principles of Electrical and Electronic Engineering, Faculty of Electrical and Computer Engineering, Technische Universität Dresden, 01062 Dresden, Germany)
Abstract:
Multi-layer CNN with a large number of layers (socalled deep CNN structures) are considered in this paper. A backpropagation algorithm is used in order to find the network parameters for a sequence of operations. The proposed learning method is able to train and optimise CNN programs that are suitable for the implementation on state-of-the-art digital designs.