Version 1.2.0
sebastian-lapuschkin
released this
17 Nov 14:23
·
159 commits
to master
since this release
Version 1.2.0 is done. Pretty much the same as 1.2.0-rc1, but better!
New in this version:
For python and matlab:
- Conv-Layer support and sum- and maxpooling have been implemented
- rudimentary network training support for all existing layers
- pre-setting lrp decomposition parameters per layer implemented
- w² and flat weight decompositions implemented for all layers (where applicable)
- demo code demonstrating LRP on LeNet-5, showing off the new features
- a slight change in the plain text model description. Backwards-compatibility for older toolbox versions is ensured.
Caffe:
- heatmapping applications producing minimal outputs have been implemented. Instead of writing out the network input and render heatmaps as images, only plain text relevance maps and the top-10 network predictions are produced per sample.
- w² and flat weight decomposition methods implemented, including a layer selection index whilch allows for a treatment with either w² or flat decomposition for all layers blow (inclusive) this layer index, and either eps- or alpha-decomposition for all upper layers. This can be used to control the resolution and semantics of the explanatory heatmaps. (See http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7532763)