keras-vis

keras-vis: Keras visualization toolkit. keras-vis is a high-level toolkit for visualizing and debugging your trained keras neural net models. Currently supported visualizations include: Activation maximization; Saliency maps; Class activation maps; All visualizations by default support N-dimensional image inputs. i.e., it generalizes to N-dim image inputs to your model. The toolkit generalizes all of the above as energy minimization problems with a clean, easy to use, and extendable interface. Compatible with both theano and tensorflow backends with ’channels_first’, ’channels_last’ data format.

References in zbMATH (referenced in 1 article )

Showing result 1 of 1.
Sorted by year (citations)

  1. Zhang, Yimeng; Lee, Tai Sing; Li, Ming; Liu, Fang; Tang, Shiming: Convolutional neural network models of V1 responses to complex patterns (2019)