Alternatives and similar repositories for CNN_VGG19_CUDA

Users that are interested in CNN_VGG19_CUDA are comparing it to the libraries listed below

• xingyul / sparse-winograd-cnn
  Efficient Sparse-Winograd Convolutional Neural Networks (ICLR 2018)
  ☆193Updated 6 years ago
• vinx13 / tvm-cuda-int8-benchmark
  Benchmark of TVM quantized model on CUDA
  ☆111Updated 5 years ago
• xuqiantong / CUDA-Winograd
  Fast CUDA Kernels for ResNet Inference.
  ☆180Updated 6 years ago
• nephashi / DeepCompression
  implementation of Iterative Pruning for Deep neural network [Han2015].
  ☆40Updated 7 years ago
• ex4sperans / pruning_with_tensorflow
  I demonstrate how to compress a neural network using pruning in tensorflow.
  ☆78Updated 8 years ago
• TianzhongSong / Tensorflow-quantization-test
  Tensorflow quantization (float32-->int8) inference test
  ☆75Updated 7 years ago
• AojunZhou / Incremental-Network-Quantization
  Caffe Implementation for Incremental network quantization
  ☆191Updated 7 years ago
• IntelLabs / SkimCaffe
  Caffe for Sparse Convolutional Neural Network
  ☆237Updated 2 years ago
• julianfaraone / SYQ
  This repository represents training examples for the CVPR 2018 paper "SYQ:Learning Symmetric Quantization For Efficient Deep Neural Netwo…
  ☆31Updated 6 years ago
• whitelok / tvm-lesson
  动手学习TVM核心原理教程
  ☆63Updated 4 years ago
• xu3kev / neural-networks-quantization-notes
  ☆66Updated 6 years ago
• slothkong / DNN-Pruning
  A pyCaffe implementaion of the 2017 ICLR's "Pruning Filters for Efficient ConvNets" publication
  ☆43Updated 7 years ago
• TropComplique / trained-ternary-quantization
  Reducing the size of convolutional neural networks
  ☆112Updated 7 years ago
• AngusG / tensorflow-xnor-bnn
  BinaryNets in TensorFlow with XNOR GEMM op
  ☆154Updated 8 years ago
• fengfu-chris / caffe-twns
  Implementation of Ternary Weight Networks In Caffe
  ☆63Updated 8 years ago
• younghwanoh / impl-pruning-caffemodel
  Simple pruning example using Caffe
  ☆33Updated 8 years ago
• boluoweifenda / WAGE
  Code example for the ICLR 2018 oral paper
  ☆152Updated 7 years ago
• CSshengxy / MEC
  ICML2017 MEC: Memory-efficient Convolution for Deep Neural Network C++实现(非官方)
  ☆17Updated 6 years ago
• BertMoons / QuantizedNeuralNetworks-Keras-Tensorflow
  Quantized Neural Networks - networks trained for inference at arbitrary low precision.
  ☆147Updated 7 years ago
• microsoft / LQ-Nets
  LQ-Nets: Learned Quantization for Highly Accurate and Compact Deep Neural Networks
  ☆242Updated 3 years ago
• tlc-pack / tophub
  tophub autotvm log collections
  ☆69Updated 2 years ago
• deep-fry / mayo
  Mayo: Auto-generation of hardware-friendly deep neural networks. Dynamic Channel Pruning: Feature Boosting and Suppression.
  ☆112Updated 5 years ago
• masahi / tvm-winograd
  Test winograd convolution written in TVM for CUDA and AMDGPU
  ☆41Updated 7 years ago
• FrozenGene / tvm-tutorial
  TVM tutorial
  ☆66Updated 6 years ago
• yeshaokai / ADMM-NN
  ☆36Updated 6 years ago
• wenwei202 / caffe
  Caffe for Sparse and Low-rank Deep Neural Networks
  ☆381Updated 5 years ago
• zhaoweicai / hwgq
  Caffe implementation of accurate low-precision neural networks
  ☆118Updated 7 years ago
• cwlacewe / netscope
  This is a CNN Analyzer tool, based on Netscope by dgschwend/netscope
  ☆42Updated 7 years ago
• may0324 / DeepCompression-caffe
  Caffe for Deep Compression
  ☆239Updated 7 years ago
• submission2019 / cnn-quantization
  Quantization of Convolutional Neural networks.
  ☆247Updated last year