Harnessing AI to help solve some of the world’s greatest challenges
Lymphoma lesion segmentation and quantitation plays a pivotal role in the diagnosis, treatment planning, and monitoring of lymphoma patients. Accurate segmentation allows for the precise delineation of pathological regions, aiding clinicians in assessing disease extent and progression. Moreover, lesion quantitation,…
The Damage Assessment Visualizer leverages satellite imagery from a disaster region to visualize conditions of building and structures before and after a disaster. It includes a visual layer on top of the satellite images which predicts the extent of damage…
This is a lightweight web-interface for creating and sharing vector annotations over satellite/aerial imagery scenes.
Source code of BindVAE paper on Variational Auto Encoders for learning binding signatures of transcription factors. https://genomebiology.biomedcentral.com/articles/10.1186/s13059-022-02723-w
Microsoft is working to make data that is relevant to important social problems as open as possible, including by contributing open data ourselves. The Data for Society resource center provides access to Microsoft’s open datasets, resources, and tools to make…
The goal of this project is to use audio recordings and corresponding annotations to build an automatic classifier for calls from four different species of blue whales, and to estimate the total number of calls from each population in the…
A repository for training models from high-resolution aerial imagery and a dataset of predicted poultry barns across the United States.
The Solar Farms Mapping release is an artificial intelligence dataset for solar energy locations in India – a spatially explicit machine learning model to map utility-scale solar projects across India using freely available satellite imagery.
This project provides code to train semantic segmentation models for pulmonary lesions segmentation from Computer Tomography (CT) scans. Furthermore, we present a multitask model for joint segmentation of different classes of pulmonary lesions present in COVID-19 infected lungs.
