LightNet: A Versatile, Standalone Matlab-based Environment for Deep Learning
This provides a user-friendly tool for researchers and practitioners in fields like computer vision and NLP who prefer Matlab, though it is incremental as it adapts existing deep learning concepts to a specific platform.
The authors tackled the need for an accessible deep learning framework by developing LightNet, a lightweight, standalone Matlab-based environment that supports major architectures like MLP, CNN, and RNN, and demonstrated its versatility through applications in computer vision, NLP, and robotics.
LightNet is a lightweight, versatile and purely Matlab-based deep learning framework. The idea underlying its 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 computation, and the switch between them is straightforward. Different applications in computer vision, natural language processing and robotics are demonstrated as experiments.