Les fonctionnalités principales de automan000/convolution_lstm_pytorch sont : Convolutional Neural Networks (CNNs).
Les alternatives open-source à automan000/convolution_lstm_pytorch incluent : aaron-xichen/pytorch-playground — Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet,… bamos/densenet.pytorch — A PyTorch implementation of DenseNet. bgshih/crnn — Convolutional Recurrent Neural Network. d-li14/octconv.pytorch. edgarriba/examples. 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