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bcnn-keras-clean

Bilinear CNN implementation in keras.

breakhist-dataset-image-classification

BreakHist Dataset contains histopathological images of eight types of breast cancer, including four benign cancer and for malignant cancer. In this project, I have trained and fined tuned many of the existing CNN models to get over 80% accuracy in multi-class classification.

breast-cancer-classification

Breast Cancer Classification using CNN and transfer learning

cbam-keras

CBAM implementation on Keras

ecanet

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

emergencynet

A small deep learning model based on atrous convolutional feature fusion for the application of emergency response.

frcnn_cad

Computer aided detection using Faster-RCNN

image-classification

This project is based on image classification using ensemble learning having three individual base models - Convolutional Neural Network (CNN), Long-Short Term Memory (LSTM), Multi-Layer Perceptron (MLP).

insights-into-few-shot-learning-for-scene-classification

keras-attention-augmented-convs

Keras implementation of Attention Augmented Convolutional Neural Networks

keras-cnn

ConvNets created with Keras.

keras-vgg16-places365

Keras code and weights files for the VGG16-places365 and VGG16-hybrid1365 CNNs for scene classification

landcover_classification

Determine land use and land cover classification based on Sentinel-2 satellite images with state-of-the-art performance 🛰

mias

Mammographic Image Classification with Deep Fusion Learning

mias_preprocess

MATLAB scripts for mammographic image (MIAS dataset) preprocessing

multi-scale-curriculum

Code for Paper: Multi Scale Curriculum CNN for Context-Aware Breast MRI Malignancy Classification

pay-more-attention

Code of paper 《Remote Sensing Image Scene Classification Based on an Enhanced Attention Module》

remote-sensing-image-classification-via-improved-cross-entropy-loss-and-transfer-learning-strategy

Remote Sensing Image Classification via Improved Cross-Entropy Loss and Transfer Learning Strategy Based on Deep Convolutional Neural Networks

remote-sensing-scene-classification

For the remote sensing scene classification task in complex background, we proposed a lightweight convolutional neural network with bilinear feature extraction structure. The idea of branch feature fusion was proposed to fuse the extracted features of different branches.

scene-classification

Scene Classification With Recurrent Attention of VHR Remote Sensing Images

skal

SKAL for remote sensing scene image classification

ssun

Spectral-Spatial Unified Networks for Hyperspectral Image Classification