closing the gap between open source and proprietary

April 25th, 2014

In 0.6 release, ccv’s deep learning based image classifier achieved 16.26% top-5 missing rate on imageNet 2010. However, the state of the art uses imageNet 2012 data set as the standard, and it is hard to do apple to orange comparison.

For the past 3 weeks, I was able to obtain the imageNet 2012 dataset, therefore, do the apple to apple comparison with the state of the art.

The newly trained data model on imageNet 2012 was able to obtain 16.22% top-5 missing rate on imageNet 2012 dataset, which is about 3% better than Caffe’s implementation, and about 0.55% shying away from 1-convnet implementation from OverFeat. This implementation is still 5% behind the state of the art Clarifai though.

This is a good step towards closing the gap between open source implementation and proprietary implementation.

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