awesome-multimodal-ml

Reading list for research topics in multimodal machine learning

cnn-3d-images-tensorflow

3D image classification using CNN (Convolutional Neural Network)

covid-chestxray-dataset

We are building an open database of COVID-19 cases with chest X-ray or CT images.

ctspine1k

A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography

dcm2niix

dcm2nii DICOM to NIfTI converter: compiled versions available from NITRC

hmdb_dataset

image-and-text-fusion-for-upmc-food-101-using-bert-and-cnns

improvelungcancerdetection

In the United States, lung cancer strikes 225,000 people every year, and accounts for $12 billion in health care costs. Early detection is critical to give patients the best chance at recovery and survival. One year ago, the office of the U.S. Vice President spearheaded a bold new initiative, the Cancer Moonshot, to make a decade's worth of progress in cancer prevention, diagnosis, and treatment in just 5 years. In 2017, the Data Science Bowl will be a critical milestone in support of the Cancer Moonshot by convening the data science and medical communities to develop lung cancer detection algorithms. Using a data set of thousands of high-resolution lung scans provided by the National Cancer Institute, participants will develop algorithms that accurately determine when lesions in the lungs are cancerous. This will dramatically reduce the false positive rate that plagues the current detection technology, get patients earlier access to life-saving interventions, and give radiologists more time to spend with their patients. This year, the Data Science Bowl will award $1 million in prizes to those who observe the right patterns, ask the right questions, and in turn, create unprecedented impact around cancer screening care and prevention. The funds for the prize purse will be provided by the Laura and John Arnold Foundation.

kl-fusion

code for our ICML 2020 paper “Model Fusion with Kullback–Leibler Divergence”, S. Claici, M. Yurochkin, S. Ghosh and J. Solomon.

ldachuan

Transform

medicalzoopytorch

A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation

muleeg

Official implementation of our MICCAI 2022 paper "mulEEG: A Multi-View Representation Learning on EEG Signals"

mvdata

Data sets for multi-view learning.

neural-lp

Differentiable Learning of Logical Rules for Knowledge Base Reasoning

pytorch-classification-uncertainty

This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"

u2pl

[CVPR 2022] Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels

wenn

Multidimensional Uncertainty-Aware Evidential Neural Networks ( AAAI2021)