Analyzing Classifiers: Fisher Vectors and Deep Neural Networks

CVPR 2016 Sebastian BachAlexander BinderGrégoire MontavonKlaus-Robert MüllerWojciech Samek

Fisher Vector classifiers and Deep Neural Networks (DNNs) are popular and successful algorithms for solving image classification problems. However, both are generally considered `black box' predictors as the non-linear transformations involved have so far prevented transparent and interpretable reasoning... (read more)

PDF Abstract CVPR 2016 PDF CVPR 2016 Abstract


No code implementations yet. Submit your code now

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper

🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet