Research
Discover an index of datasets, SDKs, APIs and open-source tools developed by Microsoft researchers and shared with the global academic community below. These experimental technologies—available through Azure AI Foundry Labs (opens in new tab)—offer a glimpse into the future of AI innovation.
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…
FastSeq provides efficient implementation of popular sequence models (e.g. Bart, ProphetNet) for text generation, summarization, translation tasks etc. It automatically optimizes inference speed based on popular NLP toolkits (e.g. FairSeq and HuggingFace-Transformers) without accuracy loss.
FS-Mol is A Few-Shot Learning Dataset of Molecules, containing molecular compounds with measurements of activity against a variety of protein targets. The dataset is presented with a model evaluation benchmark which aims to drive few-shot…
oZKS (Ordered Zero-Knowledge Set) is a library that provides an implementation of an Ordered (and Append Only) Zero-Knowledge Set.
AI for Earth project, in collaboration with the Wildlife Conservation Society Colombia (WCS Colombia (opens in new tab)) to create up-to-date land cover maps of the Orinoquía (opens in new tab) region in Colombia. We used…
Pilot Microsoft Cognitive Services to unlock the strategic value of UN unstructured content by building on AI and semantic technologies.
This project aims to predict the probability of leprosy using skin lesion images and clinical data (as compared to the diagnosis of dermatologists). This model is provided for research and development use only. The model…
A Microsoft AI for Humanitarian Action study in collaboration with the NLRC 510 global initiative. In this study, we leverage high-resolution satellite imagery to conduct building footprint segmentation and train a classifier to assign each…