Abstract
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Highlights
It is received wisdom that biological visual systems outmatch current artificial systems at complex visual tasks like object recognition
It is widely believed that tolerance ("invariance") to identity-preserving image variation is critical, systematic comparisons of state-of-the-art artificial visual representations almost always rely on "natural" image databases that can fail to probe the ability of a recognition system to solve the invariance problem [Pinto et al.]
To understand how well current state-of-the-art visual representations perform relative to each other, relative to low-level neuronal representations, and relative to high-level representations, we tested all of these representations on a common set of visual object recognition tasks that directly engage the invariance problem
Summary
It is received wisdom that biological visual systems outmatch current artificial systems at complex visual tasks like object recognition. McGovern Inst/Dept of Brain & Cog Sci, MIT Rowland Institute, Harvard Because artificial systems are improving every day, they may surpass human performance some day.
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