Limitations of Deep Learning for Vision, and How We Might Fix Them

Limitations of Deep Learning for Vision, and How We Might Fix Them History of Deep Learning We are witnessing the third rise of deep learning. The first two waves — 1950s–1960s and 1980s–1990s — generated considerable excitement but slowly ran out of steam, since these neural networks neither achieved their promised performance gains nor aided our understanding of biological vision systems. The th

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ビジョンのための深層学習の限界とそれらをどう修正するか

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"real world images is combinatorially large, and so it is hard for any dataset ... to be representative of the complexity of the real world." "Compositionality ... substructures and the grammars can be learned from finite amounts of data but will generalize to combinatorial situations."