Training Very Deep Neural Networks Without Skip-Connections
Les fonctionnalités principales de szagoruyko/diracnets sont : Convolutional Neural Networks (CNNs).
Les alternatives open-source à szagoruyko/diracnets incluent : aaron-xichen/pytorch-playground — Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet,… automan000/convolution_lstm_pytorch. bamos/densenet.pytorch — A PyTorch implementation of DenseNet. bgshih/crnn — Convolutional Recurrent Neural Network. d-li14/octconv.pytorch. 1zb/deformable-convolution-pytorch — PyTorch implementation of Deformable Convolution.
Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)
PyTorch implementation of Deformable Convolution
