qujunrong

Hyperspectral-Image-Segmentation

Semantic Segmentation of HyperSpectral Images using a U-Net with Depthwise Separable Convolutions

DenoisingAutoEncoder

Python implementation of Stacked Denoising Autoencoders for unsupervised learning of high level feature representation

Iris-Segmentation-and-model-Interpretation

Pixel wise segmentation of Iris using Encoder-Decoder architecture and the interpretation of the model's decision using Layer-wise Relevance Propagation (LRP) algorithm.

sentinel1ice

Ice/water classification of Sentinel1 SAR data

Automatic-Target-Classification-In-SAR-Images-Using-Convolutional-Neural-Networks

SAR -> Synthetic Aperture Radar. This project is based on predicting the accuracy of the testing data set over the training data set using the MSTAR(Moving and Stationary Target Acquisition and Recognition) database and plotting the graph of the Results.csv file.

Semi-SAE-release

A DEMO for "Semisupervised Stacked Autoencoder With Cotraining for Hyperspectral Image Classification" (Xue et al., TGRS, 2019)

face_classification

Real-time face detection and emotion/gender classification using fer2013/imdb datasets with a keras CNN model and openCV.

deeplearningbook-chinese

Deep Learning Book Chinese Translation

models

Models and examples built with TensorFlow

Basic_CNNs_TensorFlow2

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

Bag_of_Tricks_for_Image_Classification_with_Convolutional_Neural_Networks

experiments on Paper <Bag of Tricks for Image Classification with Convolutional Neural Networks> and other useful tricks to improve CNN acc

residual-attention-network

Residual Attention Network for Image Classification

DCNN

self implemented pytorch version of the work: DENSELY CONNECTED CNN WITH MULTI-SCALE FEATURE ATTENTION

ECANet

Code for ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks

channel-attention

Gluon implementation of channel-attention modules: SE, ECA, GCT

Deep-learning-based-image-classification-using-SENet-attention-module

SimCLR-with-CBAM-TF-Keras

SimCLR self-supervised model with CBAM attention module implementation.

CBAM-vs-SENet-Comparison

Ensemble-of-Multi-Scale-CNN-for-Dermatoscopy-Classification

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.

Deep-Learning-Image-Classification-Models-Based-CNN-or-Attention

This project organizes classic images classification neural networks based on convolution or attention, and writes training and inference python scripts

cbam_cnn_architectures_image_classification

Spatial and Channel Attention in CNN Architectures for Image Classification task

classification

This is a classification project in Pytorch. Models include densenet,DPN,Inception, ResneXt,SeNet.

classification_models

Classification models trained on ImageNet. Keras.

SENet_ResNeXt_Remote_Sensing_Scene_Classification

SENet ResNeXt and Resnet for High-resolution Remote Sensing Scene Clasisification

Classification_model

The mainstream model of image classification is realized in this work. LeNet、VGG、Inception v1、v2、v3、v4、ResNet、SENet、ShuffleNet、MobileNet、GhostNet...

image-classification

here are some classic networks for image classification implement by pytorch

DANet

Dual Attention Network for Scene Segmentation (CVPR2019)

Polarimetric-Scattering-Coding

SKNet

try to implement the CVPR 2019 paper "Selective Kernel Networks" by PyTorch

FusAtNet-Dual-Attention-based-SpectroSpatial-Multimodal-Fusion-Network-for-Hyperspectral-and-LiDAR-

The repository contains relevant dataset and keras code for the paper, "FusAtNet: Dual Attention based SpectroSpatial Multimodal Fusion Network for Hyperspectral and LiDAR Classification"