Tensorview
Xinyu Chen, Qiang Guan, Xin Liang, Li‐Ta Lo, Simon M. Su, Trilce Estrada, James Paul Ahrens · 2017
Convolutional Neural Networks(CNNs) have been widely used in visual recognition tasks recently. Previous works visualize learning features at different layers to help people to understand how CNNs learn visual recognition tasks. However they only provide qualitative description and do not help to accelerate the training process. We present TensorView to enable Paraview to visualize the evolution of CNNs. TensorView provides both qualitative and quantitative visualization that help understand the learning procedure, tune the learning parameters, direct merging and pruning of neural networks.