Accelerating convolution using numba, cupy and xnor in python
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Feb 16, 2020 - Jupyter Notebook
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Accelerating convolution using numba, cupy and xnor in python
cuda parallelization numba fast-convolutions popcount binary-convolutions convolution2d xnor-convolutions cupy vectorized-computation im2col bitpacking python-cuda
Advance Patch Matcher Implementation. Matching patches with high accuracy and short time conditions using simplified SIFT algorithm and RANSAC outlier filtering.
python algorithm image-processing convolution edge-detection patch sift sift-algorithm ransac gauss-blur convolution2d non-maximum-suppression sift-descriptors sift-features ransac-algorithm psiml harris-corner-detector patch-matching
This is a simple convolution implementation both for CPU_only and GPU_only (using CUDA)
Neural networks
artificial-neural-networks convolutional-neural-networks mlp neuralnetwork convolution2d softmax arctan relu numpy-neural-network batchnormalization maxpool2d
Train a deep neural network to drive a car like you!
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