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eladhoffer/convNet.pytorch

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ConvNet.pytorch

Features

  • Computer Vision Models - Training examples for deep convolutional networks on standard datasets.
  • Model Implementations - Training examples for deep convolutional networks.

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Ver las 30 alternativas a ConvNet.pytorch→

Preguntas frecuentes

¿Cuáles son las características principales de eladhoffer/convnet.pytorch?

Las características principales de eladhoffer/convnet.pytorch son: Computer Vision Models, Model Implementations.

¿Qué alternativas de código abierto existen para eladhoffer/convnet.pytorch?

Las alternativas de código abierto para eladhoffer/convnet.pytorch incluyen: amdegroot/ssd.pytorch — This is a PyTorch object detection framework that implements the Single Shot MultiBox Detector for identifying and… aosokin/biogans. aaron-xichen/pytorch-playground — Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet,… 1zb/deformable-convolution-pytorch — PyTorch implementation of Deformable Convolution. 1adrianb/face-alignment — This is a PyTorch-based computer vision library for detecting 2D and 3D facial landmark coordinates. It functions as a… bamos/densenet.pytorch — A PyTorch implementation of DenseNet.