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Effective and High Computing Algorithms for Convolution Neural Networks
2018
International Journal of Engineering & Technology
Training a large set of data takes GPU days using Deep convolution neural networks which are a time taking process. Self-driving cars require very low latency for pedestrian detection. Image recognition constrained by limited processing resources for mobile phones. The computation speed of the training set determines that in these situations convolution neural networks was a success. For large filters, Conventional Faster Fourier Transform based convolution is preferably fast, yet in case of
doi:10.14419/ijet.v7i3.31.18203
fatcat:24m3ebi5dbccjg5l7j6pdb6e7q