Squeeze-and-Excitation Networks

PyTorch implementation of SENet

This is a pytorch repository of YOLOv4, attentive YOLOv4 and mobilenet YOLOv4 with PASCAL VOC and COCO

Classification models trained on ImageNet. Keras.

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)

PyTorch implementation of CNNs for CIFAR benchmark

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

a pytorch lib with state-of-the-art architectures, pretrained models and real-time updated results

A Caffe Re-Implementation of SENet

CBAM implementation on TensowFlow

Variant VNet family

SENet implementation on TensorFlow Slim

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

CBAM implementation on TensorFlow Slim

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

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.

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.

Convert Caffe models to ONNX.

可以训练yolov5(v6.0)、yolox、小型网络，添加注意力机制