There are 3 repositories under senet topic.
This is a pytorch repository of YOLOv4, attentive YOLOv4 and mobilenet YOLOv4 with PASCAL VOC and COCO
Classification models trained on ImageNet. Keras.
a pytorch lib with state-of-the-art architectures, pretrained models and real-time updated results
Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
Simple Tensorflow implementation of "Squeeze and Excitation Networks" using Cifar10 (ResNeXt, Inception-v4, Inception-resnet-v2)
A tensorflow2 implementation of some basic CNNs(MobileNetV1/V2/V3, EfficientNet, ResNeXt, InceptionV4, InceptionResNetV1/V2, SENet, SqueezeNet, DenseNet, ShuffleNetV2, ResNet).
CBAM implementation on TensowFlow
CBAM implementation on TensorFlow Slim
An open-source toolkit which is full of handy functions, including the most used models and utilities for deep-learning practitioners!
This is a SE_DenseNet which contains a senet (Squeeze-and-Excitation Networks by Jie Hu, Li Shen, and Gang Sun) module, written in Pytorch, train, and eval codes have been released.
Baseline classifiers on the polluted MNIST dataset, SJTU CS420 course project
SENet implementation on TensorFlow Slim
Convert Caffe models to ONNX.
Fully supervised binary classification of skin lesions from dermatoscopic images using an ensemble of diverse CNN architectures (EfficientNet-B6, Inception-V3, SEResNeXt-101, SENet-154, DenseNet-169) with multi-scale input.
Gluon implementation of channel-attention modules: SE, ECA, GCT
This is a torchvision style CNN models collection based on pytorch.
A Tensorflow 2.0 implementation of Squeeze and Excitation ResNet50 Networks (SEResNet)
here are some classic networks for image classification implement by pytorch
DenseShuffleNet for Semantic Segmentation using Caffe for Cityscapes and Mapillary Vistas Dataset
In this repository, I released senet-densenet training codes and output files. And it refer to another repository(https://github.com/zhouyuangan/SE_DenseNet), which repository I had made some notes in.
Squeeze-and-Excitation Networks, a new architecture building block proposed by WMW team at ILSVRC2017 challenges