On Fast Deep Nets for AGI Vision.
AGI'11: Proceedings of the 4th international conference on Artificial general intelligence(2011)
摘要
Artificial General Intelligence will not be general without computer vision. Biologically inspired adaptive vision models have started to outperform traditional pre-programmed methods: our fast deep / recurrent neural networks recently collected a string of 1st ranks in many important visual pattern recognition benchmarks: IJCNN traffic sign competition, NORB, CIFAR10, MNIST, three ICDAR handwriting competitions. We greatly profit from recent advances in computing hardware, complementing recent progress in the AGI theory of mathematically optimal universal problem solvers.
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关键词
adaptive vision model,computer vision,recent advance,recent progress,AGI theory,Artificial General Intelligence,ICDAR handwriting competition,IJCNN traffic sign competition,important visual pattern recognition,optimal universal problem solvers,AGI vision,fast deep net
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