GitHub / sdamadi / image-classification
Comprehensive image classification for training multilayer perceptron (MLP), LeNet, LeNet5, conv2, conv4, conv6, VGG11, VGG13, VGG16, VGG19 with batch normalization, ResNet18, ResNet34, ResNet50, MobilNetV2 on MNIST, CIFAR10, CIFAR100, and ImageNet1K.
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PURL: pkg:github/sdamadi/image-classification
Stars: 4
Forks: 0
Open issues: 0
License: mit
Language: Python
Size: 46.1 MB
Dependencies parsed at: Pending
Created at: about 4 years ago
Updated at: about 1 year ago
Pushed at: almost 4 years ago
Last synced at: 4 months ago
Topics: adam, automatic-mixed-precision, cifar, distributed-training, hyperparameters, image-classification, imagenet, learning-rate-scheduling, learning-rate-warmup, logging, mnist, pytorch, pytorch-implementation, resnet, sgd, small-convolutional, tensorboard, tensorboard-pytorch, training, vgg