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Not at all! I'd love for vision to be solved, no matter what the method. I'm more than happy to move onto another field if that's the case. But I don't think i
by apu 15y ago
Not at all! I'd love for vision to be solved, no matter what the method. I'm more than happy to move onto another field if that's the case.
But I don't think it is. MNIST data is not particularly challenging. It's great that deep learning methods work there -- they must be doing something right.
Come back and taunt me when deep learning methods start getting state-of-the-art results on, e.g., Pascal VOC: http://pascallin.ecs.soton.ac.uk/challenges/VOC/ http://pascallin.ecs.soton.ac.uk/challenges/VOC/
- marshallp 15y agogetting best results on the harder vision challenges is simply a matter of let the computers run long enough. Collobert's work for example took 3 months of training. I don't see why vision challenges should any different. Perhaps the vision researchers, of which there are many more people than the few deep learning groups should try it.