LightNet

Efficient, transparent deep learning in hundreds of lines of code.

LightNet is a lightweight, versatile and purely Matlab-based deep learning framework. The aim of the design is to provide an easy-to-understand, easy-to-use and efficient computational platform for deep learning research. The implemented framework supports major deep learning architectures such as the Multilayer Perceptron Networks (MLP), Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN). LightNet supports both CPU and GPU for computation and the switch between them is straightforward. Different applications in computer vision, natural language processing and robotics are demonstrated as experiments.
This work was published as:
Chengxi Ye, Chen Zhao, Yezhou Yang, Cornelia Fermüller, and Yiannis Aloimonos. 2016. LightNet: A Versatile, Standalone Matlab-based Environment for Deep Learning. In Proceedings of the 2016 ACM on Multimedia Conference (MM '16). Amsterdam, The Netherlands, 1156-1159. (http://dl.acm.org/citation.cfm?id=2973791)