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LightNet: A Versatile, Standalone Matlab-based Environment for Deep Learning

Chengxi Ye, Chen Zhao, Yezhou Yang, Cornelia Fermuller, Yiannis Aloimonos
Computer Vision Lab, University of Maryland, College Park, MD 20740, USA
arXiv:1605.02766 [cs.LG], (9 May 2016)

@article{ye2016lightneta,

   title={LightNet:A Versatile, Standalone Matlab-based Environment for Deep Learning},

   author={Ye, Chengxi and Zhao, Chen and Yang, Yezhou and Fermuller, Cornelia and Aloimonos, Yiannis},

   year={2016},

   month={may},

   archivePrefix={"arXiv"},

   primaryClass={cs.LG}

}

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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 Multilayer Perceptron Networks (MLP), Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN). The framework also 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.
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