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Hmm I would refrain from saying DL is useful only when approaching 1 megapixel images. State of the art performance on MNIST is held by a 6 layer convnet (4 la
by ovi256 9y ago
Hmm I would refrain from saying DL is useful only when approaching 1 megapixel images.
State of the art performance on MNIST is held by a 6 layer convnet (4 layers convolutional, 2 layers FC). MNIST is just 28 x 28 grayscale images, so 768 dimensions. There are many more datasets on the same order of dimensionality. CIFAR 10/100 (32 x 32 pixel images) is also dominated by DL convnets, AFAIK.
- krosaen 9y agoSure, didn't mean to imply megapixel images were the lower threshold, just that it is more to do with the number of features and the need to automatically extract higher level features.