maftouni

Awesome-Convolutional-Attention-Mechanism-papers

The most influential papers in convolutional attention mechanisms, suitable for image classification, image and video object segmentation and tracking

Battery_Aging

binary_mask_from_json

Making binary mask images from JSON annotation

Corona_CT_Classification

COVID-19

CovidGlobal

Code & model files for Rahmandad, Lim & Sterman (2020), Estimating the global spread of COVID-19

Curated_Covid_CT

We built a large lung CT scan dataset for COVID-19 by curating data from 7 different public datasets. These datasets have been publicly used in COVID-19 diagnosis literature and proven their efficiency in deep learning applications. Therefore, the merged dataset is expected to improve the generalization ability of deep learning methods by learning from all these resources together.

Patient_Aware_Splitter

It is important not to split images of the same patient between the test and train sets to avoid overfitting. This repository splits a sample Covid/Normal classification dataset into test and train sets in a patient aware and stratified manner.

SegLoss

A collection of loss functions for medical image segmentation

maftouni/100-Days-Of-ML-Code

100 Days of ML Coding

maftouni/attention-module

Official PyTorch code for "BAM: Bottleneck Attention Module (BMVC2018)" and "CBAM: Convolutional Block Attention Module (ECCV2018)"

maftouni/awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

maftouni/datasharing

The Leek group guide to data sharing

maftouni/e3d_lstm

e3d-lstm; Eidetic 3D LSTM A Model for Video Prediction and Beyond

maftouni/LovaszSoftmax

Code for the Lovász-Softmax loss (CVPR 2018)

maftouni/machine-learning-project-walkthrough

An implementation of a complete machine learning solution in Python on a real-world dataset. This project is meant to demonstrate how all the steps of a machine learning pipeline come together to solve a problem!

maftouni/pytorch-generative-adversarial-networks

A very simple generative adversarial network (GAN) in PyTorch

maftouni/tensorflow

Computation using data flow graphs for scalable machine learning

maftouni/transparent_latent_gan

Use supervised learning to illuminate the latent space of GAN for controlled generation and edit

maftouni/UGATIT

Official Tensorflow implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation