cifar
There are 104 repositories under cifar topic.
osmr/imgclsmob
Sandbox for training deep learning networks
akamaster/pytorch_resnet_cifar10
Proper implementation of ResNet-s for CIFAR10/100 in pytorch that matches description of the original paper.
megvii-research/mdistiller
The official implementation of [CVPR2022] Decoupled Knowledge Distillation https://arxiv.org/abs/2203.08679 and [ICCV2023] DOT: A Distillation-Oriented Trainer https://openaccess.thecvf.com/content/ICCV2023/papers/Zhao_DOT_A_Distillation-Oriented_Trainer_ICCV_2023_paper.pdf
BIGBALLON/CIFAR-ZOO
PyTorch implementation of CNNs for CIFAR benchmark
ildoonet/pytorch-randaugment
Unofficial PyTorch Reimplementation of RandAugment.
prlz77/ResNeXt.pytorch
Reproduces ResNet-V3 with pytorch
hongyi-zhang/mixup
Implementation of the mixup training method
gaohuang/MSDNet
Multi-Scale Dense Networks for Resource Efficient Image Classification （ICLR 2018 Oral）
felixgwu/img_classification_pk_pytorch
Quickly comparing your image classification models with the state-of-the-art models (such as DenseNet, ResNet, ...)
conan7882/GoogLeNet-Inception
TensorFlow implementation of GoogLeNet and Inception for image classification.
zlmzju/fusenet
Deep fusion project of deeply-fused nets, and the study on the connection to ensembling
csinva/gan-vae-pretrained-pytorch
Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.
ethanhe42/resnet-cifar10-caffe
ResNet-20/32/44/56/110 on CIFAR-10 with Caffe
ma-xu/Open-Set-Recognition
Open Set Recognition
voldemortX/DST-CBC
Implementation of our Pattern Recognition paper "DMT: Dynamic Mutual Training for Semi-Supervised Learning"
visresearch/patchmix
The official implementation of paper: "Inter-Instance Similarity Modeling for Contrastive Learning"
FreeformRobotics/Divide-and-Co-training
[TIP 2022] Towards Better Accuracy-efficiency Trade-offs: Divide and Co-training. Plus, an image classification toolbox includes ResNet, Wide-ResNet, ResNeXt, ResNeSt, ResNeXSt, SENet, Shake-Shake, DenseNet, PyramidNet, and EfficientNet.
bytesc/Image_Classify_WebGUI_CIFAR10
✨基于卷积神经网络(CNN)和CIFAR10数据集的图像智能分类 Web 应用 Intelligent Image Classification Web Applcation based on Convolutional Neural Networks and the CIFAR10 Dataset✨🚩 (with README in English) 📌含在线demo：图像分类可视化界面，快速部署深度学习模型为网页应用，Web预测系统，决策支持系统(DSS)，图像分类前端网页，图像分类Demo展示-Pywebio。AI人工智能图像分类-Pytorch。CIFAR10数据集，小模型。100%纯Python代码，轻量化，易复现
hunto/image_classification_sota
Training ImageNet / CIFAR models with sota strategies and fancy techniques such as ViT, KD, Rep, etc.
dongyp13/Stochastic-Quantization
Training Low-bits DNNs with Stochastic Quantization
hyperion-ml/hyperion
Python toolkit for speech processing
dnlcrl/deep-residual-networks-pyfunt
Python implementation of "Deep Residual Learning for Image Recognition" (http://arxiv.org/abs/1512.03385 - MSRA, winner team of the 2015 ILSVRC and COCO challenges).
visresearch/aps
The official implementation of "Asymmetric Patch Sampling for Contrastive Learning"
EN10/CIFAR
CIFAR 10 image dataset
Queequeg92/SE-Net-CIFAR
SE-Net Incorporates with ResNet and WideResnet on CIFAR-10/100 Dataset.
MIC-DKFZ/image_classification
:dart: Deep Learning Framework for Image Classification & Regression in Pytorch for Fast Experiments
ritchieng/wideresnet-tensorlayer
Wide Residual Networks implemented in TensorLayer and TensorFlow.
hunto/DyRep
Official implementation for paper "DyRep: Bootstrapping Training with Dynamic Re-parameterization", CVPR 2022
mateuszbuda/ALL-CNN
Striving for Simplicity: The All Convolutional Net (All-CNN-C)
yui0/catseye
Neural network library written in C and Javascript
ShivamShrirao/dnn_from_scratch
A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).
lionelmessi6410/tensorflow2-cifar
95.76% on CIFAR-10 with TensorFlow2
tajanthan/pmf
Proximal Mean-field for Neural Network Quantization
SeongwoongCho/adversarial-autoaugment-pytorch
Unofficial Pytorch Implementation Of AdversarialAutoAugment(ICLR2020)
ismail31416/LumiNet
The official implementation of LumiNet: The Bright Side of Perceptual Knowledge Distillation https://arxiv.org/abs/2310.03669