What is Reddit's opinion of Nippler?

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I found this. I also found this, which I think is hilarious. It's amazing to think that all the recent advances in machine vision and facial recognition can be equally applicable to to finding nipples, and penises.

https://play.google.com/store/apps/details?id=com.boxcar2d.nippler

I created this app with a model I trained on a CNN with varying layers of pooling and convolution. The confidence can be adjusted. The colors represent the prediction confidence: 99% magenta, 95%red, 90% orange, 80% yellow, 70% blue, 60% gray, 50% cyan.

https://play.google.com/store/apps/details?id=com.boxcar2d.nippler

I created this app with a model I trained on a CNN with varying layers of pooling and convolution. The confidence can be adjusted. The colors represent the prediction confidence: 99% magenta, 95%red, 90% orange, 80% yellow, 70% blue, 60% gray, 50% cyan.

Gonna add some references:

Caffe

ImageNet Classification with Deep Convolutional Neural Networks, Krizhevsky 2012

Deep neural networks are easily fooled, Nguyen 2014

Selective Search for object Recognition, Uijlings 2013

Combining efficient object localization and image classification, Harzallah 2009

and of course http://deeplearning.net/reading-list/

http://i.imgur.com/ha8ejds.jpg

Made this app to detect nipples. testing it. Nippler: https://play.google.com/store/apps/details?id=com.boxcar2d.nippler

This submission to Machine Learning was originally posted by deepPurpleHaze, on Thu 23-04-15.

It has 671 points.

The top comment of the submission was:

>https://play.google.com/store/apps/details?id=com.boxcar2d.nippler > >I created this app with a model I trained on a CNN with varying layers of pooling and convolution. The confidence can be adjusted. The colors represent the prediction confidence: 99% magenta, 95%red, 90% orange, 80% yellow, 70% blue, 60% gray, 50% cyan. > > >Gonna add some references: > >Caffe > >ImageNet Classification with Deep Convolutional Neural Networks, Krizhevsky 2012 > >Deep neural networks are easily fooled, Nguyen 2014 > >Selective Search for object Recognition, Uijlings 2013 > >Combining efficient object localization and image classification, Harzallah 2009 > >and of course http://deeplearning.net/reading-list/ > > > > > > >

The comment was posted by deepPurpleHaze and has 156 points.

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