Shanqing Cai
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4c02b542a4
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[visualize-convnet] Add new example: visualize-convnet (#201)
This TensorFlow.js example demonstrates some techniques of visualizing
the internal workings of a convolutional neural network (convnet), including:
- Finding what convolutional layers' filters are sensitive to after
training: calculating maximally-activating input image for
convolutional filters through gradient ascent in the input space.
- Getting the internal activation of a convnet by uisng the
functional model API of TensorFlow.js
- Finding which part of an input image is most relevant to the
classification decision made by a convnet (VGG16 in this case),
using the gradient-based class activation map (CAM) approach.
Example screenshots:
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2019-01-23 23:30:34 -05:00 |
