resnext

qubvel/segmentation_models

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

weiaicunzai/pytorch-cifar100

Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)

bearpaw/pytorch-classification

Classification with PyTorch.

lxztju/pytorch_classification

利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码

soeaver/caffe-model

Caffe models (including classification, detection and segmentation) and deploy files for famouse networks

qubvel/classification_models

Classification models trained on ImageNet. Keras.

GoogleCloudPlatform/keras-idiomatic-programmer

Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework

taki0112/SENet-Tensorflow

Simple Tensorflow implementation of "Squeeze and Excitation Networks" using Cifar10 (ResNeXt, Inception-v4, Inception-resnet-v2)

BIGBALLON/CIFAR-ZOO

PyTorch implementation of CNNs for CIFAR benchmark

calmiLovesAI/Basic_CNNs_TensorFlow2

A tensorflow2 implementation of some basic CNNs(MobileNetV1/V2/V3, EfficientNet, ResNeXt, InceptionV4, InceptionResNetV1/V2, SENet, SqueezeNet, DenseNet, ShuffleNetV2, ResNet).

prlz77/ResNeXt.pytorch

Reproduces ResNet-V3 with pytorch

AllentDan/LibtorchSegmentation

A c++ trainable semantic segmentation library based on libtorch (pytorch c++). Backbone: VGG, ResNet, ResNext. Architecture: FPN, U-Net, PAN, LinkNet, PSPNet, DeepLab-V3, DeepLab-V3+ by now.

gabrielilharco/snap-n-eat

Food detection and recommendation with deep learning

tugstugi/pytorch-speech-commands

Speech commands recognition with PyTorch | Kaggle 10th place solution in TensorFlow Speech Recognition Challenge

xmuyzz/3D-CNN-PyTorch

PyTorch implementation for 3D CNN models for medical image data (1 channel gray scale images).

kobiso/CBAM-tensorflow

CBAM implementation on TensowFlow

zheng-yuwei/multi-label-classification

基于tf.keras的多标签多分类模型

prakashjayy/medium_blogs

medium blog supplementaries | Backprop | Resnet & ResNext | RNN |

d-li14/dgconv.pytorch

PyTorch implementation of Dynamic Grouping Convolution and Groupable ConvNet with pre-trained G-ResNeXt models

d-li14/regnet.pytorch

PyTorch-style and human-readable RegNet with a spectrum of pre-trained models

cxy1997/MNIST-baselines

Baseline classifiers on the polluted MNIST dataset, SJTU CS420 course project

HiKapok/TF-SENet

SE_ResNet && SE_ResNeXt with pretrained weights on ImageNet (SENet In TensorFlow)

Sakib1263/TF-1D-2D-ResNetV1-2-SEResNet-ResNeXt-SEResNeXt

Models supported: ResNet, ResNetV2, SE-ResNet, ResNeXt, SE-ResNeXt [layers: 18, 34, 50, 101, 152] (1D and 2D versions with DEMO for Classification and Regression).

velebit-ai/COVID-Next-Pytorch

COVID-Next -> Pytorch upgrade of the COVID-Net for COVID-19 detection in X-Ray images

XiaoyiHan6/Simple-CV-Pytorch-master

This code includes classification and detection tasks in Computer Vision, and semantic segmentation task will be added later.

calmiLovesAI/ResNeXt_TensorFlow2

A tensorflow2 implementation of ResNeXt(ResNeXt50, ResNeXt101).

xternalz/SDPoint

Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks

syt2/CNN

pytorch implementation of several CNNs for image classification

itisianlee/paddle-cifar100

paddle cifar100 training

AliAbbasi/Deep-3D-Semantic-Scene-Extrapolation

Deep 3D Semantic Scene Extrapolation

rohitgr7/tvmodels

Pytorch implementation of vision models.

yell/kaggle-camera

My solution to Kaggle challenge "IEEE Camera Model Identification" [top 3%]

vivekkalyan/fine-grained-image-classification

GuanqiaoDing/CNN-CIFAR10

Implement and Compare VGG, ResNet and ResNeXt on CIFAR-10

KeshavCh0udhary/HIS2.0

DeepFake Detection Web-App[Mirage Breaker] 🖥 using Deep Learning(ResNext and LSTM), Flask and ReactJs where you can predict whether a video is FAKE Or REAL along with the confidence ratio.