geifmany / cifar-vgg
VGG16 models for CIFAR-10 and CIFAR-100 using Keras
☆219Updated 3 years ago
Related projects ⓘ
Alternatives and complementary repositories for cifar-vgg
- 3.41% and 17.11% error on CIFAR-10 and CIFAR-100☆328Updated 5 years ago
- This is the PyTorch implementation of VGG network trained on CIFAR10 dataset☆346Updated 5 years ago
- Simple Tensorflow implementation of pre-activation ResNet18, 34, 50, 101, 152☆181Updated 5 years ago
- PyTorch Implementation of Weights Pruning☆184Updated 6 years ago
- Best CIFAR-10, CIFAR-100 results with wide-residual networks using PyTorch☆461Updated 4 years ago
- Wide Residual Networks in Keras☆111Updated 6 years ago
- Pytorch version for weight pruning for Murata Group's CREST project☆57Updated 6 years ago
- tensorflow implementation of Grad-CAM (CNN visualization)☆307Updated 6 years ago
- A machine learning experiment☆182Updated 7 years ago
- An implementation of "mixup: Beyond Empirical Risk Minimization"☆284Updated 7 years ago
- 2.56%, 15.20%, 1.30% on CIFAR10, CIFAR100, and SVHN https://arxiv.org/abs/1708.04552☆544Updated 4 years ago
- Cifar-10 CNN implementation using TensorFlow library with 20% error.☆91Updated 5 years ago
- TensorFlow implementations of visualization of convolutional neural networks, such as Grad-Class Activation Mapping and guided back propa…☆197Updated 6 years ago
- CNN to classify the cifar-10 database by using a vgg16 trained on Imagenet as base.☆28Updated 5 years ago
- ConvNet training using pytorch☆347Updated 3 years ago
- Wide Residual Networks (WideResNets) in PyTorch☆333Updated 3 years ago
- Implementation of Grad CAM in tensorflow☆248Updated 2 years ago
- PyTorch implementation of "Distilling the Knowledge in a Neural Network" for model compression☆59Updated 7 years ago
- Multi-Scale Dense Networks for Resource Efficient Image Classification （ICLR 2018 Oral）☆462Updated 5 years ago
- A PyTorch implementation of the iterative pruning method described in Han et. al. (2015)☆40Updated 5 years ago
- Code release for "Adversarial Robustness vs Model Compression, or Both?"☆90Updated 3 years ago
- Learning both Weights and Connections for Efficient Neural Networks https://arxiv.org/abs/1506.02626☆174Updated 2 years ago
- A Pytorch implementation of Neural Network Compression (pruning, deep compression, channel pruning)☆153Updated 4 months ago
- CondenseNet: Light weighted CNN for mobile devices☆694Updated 5 years ago
- SNIP: SINGLE-SHOT NETWORK PRUNING BASED ON CONNECTION SENSITIVITY☆111Updated 5 years ago
- PyTorch Implementation of [1611.06440] Pruning Convolutional Neural Networks for Resource Efficient Inference☆875Updated 5 years ago
- PyTorch implementation of AutoAugment.☆157Updated 4 years ago
- Baseline classifiers on the polluted MNIST dataset, SJTU CS420 course project☆69Updated 5 years ago
- Compress neural network with pruning and quantization using TensorFlow.☆105Updated 5 years ago