Large Scale Visual Recognition Challenge 2011 - Results

I don't think this proves a superiority of any algorithm against other. Just that SuperVision team did a great job on task 1 and task 2. I just would add two things: 1) There is a No Free Lunch Theorem (<a href="http://en.wikipedia.org/wiki/No_free_lunch_theorem" rel="nofollow">http://en.wikipedia.org/wiki/No_free_lunch_theorem</a>) that had been applied to pattern recognition too and that states that there is not a significative difference in performance between most pattern recognition algorithms.<p>2) There is way more chance to get an increment on performance depending of the choose of the features being used, and that seems to be the case here.

Hinton's team (SuperVision) uses an interesting 'dropout' technique. He gave a Google Tech Talk on this back in June.<p><a href="http://www.youtube.com/watch?v=DleXA5ADG78&#38;feature=plcp" rel="nofollow">http://www.youtube.com/watch?v=DleXA5ADG78&#38;feature=plcp</a><p>And an older talk that covers some of what a deep convolutional net is:<p><a href="http://www.youtube.com/watch?v=VdIURAu1-aU" rel="nofollow">http://www.youtube.com/watch?v=VdIURAu1-aU</a>

Sensational title that misrepresent the results of a competition with limited (albeit high quality) participants. There is limited information of general value in this link.

Am not sure if you can apply winner takes all for such marginal difference in error. Give a slightly different database and things go awry.<p>Check out : "Unbiased Look at Dataset Bias", A. Torralba, A. Efros,CVPR 2011.

Neural Networks officially best at object recognition <i>in this particular competition of seven teams, on two of the three tasks.</i><p>Not to take away from the accomplishment of the SuperVision team, but claim in the title seems somewhat sensationalist. Is this competition like the world cup of object recognition or something?

I found the title of this post really ironic.<p>"There is now clearly an objective answer to which inductive algorithm to use"

Just to add sense for newcomers, the original title of the thread was "Neural Networks officially best at object recognition" and most of the posts in here debated that the title was not appropriate for the link.

Congrats to the awesome folks at ISI for scoring 1st at task 3 and 2nd at task 1! Keep rocking my world.

why isn't there any solution of task 3 from team SuperVision with their Neural Nets?

*this implementation of a neural network designed for object recognition for this particular challenge

So, this is what HN posts have come to? The level of tabloid science news coverage.

The title has changes at least twice, confusing discussion. Can we have a title history on HN posts? Mutable state stinks.