Large Scale Visual Recognition Challenge 2011 - Results
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Large Scale Visual Recognition Challenge 2011 - Results
1–10 of 38 posts
Re: Large Scale Visual Recognition Challenge 2011 - Results
#2I found the title of this post really ironic.
"There is now clearly an objective answer to which inductive algorithm to use"
Re: Large Scale Visual Recognition Challenge 2011 - Results
#3Congrats to the awesome folks at ISI for scoring 1st at task 3 and 2nd at task 1! Keep rocking my world.
Re: Large Scale Visual Recognition Challenge 2011 - Results
#4I 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 (http://en.wikipedia.org/wiki/No_free_lunch_theorem) 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.
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.
Re: Large Scale Visual Recognition Challenge 2011 - Results
#5I 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 ( http://en.wikipedia.org/wiki/No_free_lunch_theorem ) that had been applied to pattern recognition too and that states that there is not a significative difference in performance between most pattern recognition algor…
To nitpick at the math: "No free lunch" results are asymptotic in the sense that they necessarily hold over the _entire_ domain of whatever problem you're trying to solve. Obviously, algorithms will and do perform differently over the relatively few inputs (compared to infinity...) that they actually encounter. It's similar to undecidability: just because a problem is generally undecidable doesn't mean you can't compute it for certain subsets of input, and compute it reasonably well (for some definition of reasonable).
Re: Large Scale Visual Recognition Challenge 2011 - Results
#6Am not sure if you can apply winner takes all for such marginal difference in error. Give a slightly different database and things go awry.
Check out : "Unbiased Look at Dataset Bias", A. Torralba, A. Efros,CVPR 2011.
Re: Large Scale Visual Recognition Challenge 2011 - Results
#7why isn't there any solution of task 3 from team SuperVision with their Neural Nets?
Re: Large Scale Visual Recognition Challenge 2011 - Results
#8I 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 ( http://en.wikipedia.org/wiki/No_free_lunch_theorem ) that had been applied to pattern recognition too and that states that there is not a significative difference in performance between most pattern recognition algor…
Have to agree that this doesn't prove anything. It is only one local contest. The title is very misleading.
Re: Large Scale Visual Recognition Challenge 2011 - Results
#9Sensational title that misrepresent the results of a competition with limited (albeit high quality) participants. There is limited information of general value in this link.
Re: Large Scale Visual Recognition Challenge 2011 - Results
#10Neural Networks officially best at object recognition in this particular competition of seven teams, on two of the three tasks.
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?