In partnership with the World Resources Institute, a global research organization that works on issues such as energy efficiency and climate change, we examined vehicle usage in developing countries. There is often a lack of critical data for developing countries on vehicle purchases and usage patterns, which is a significant gap in sustainability research.
Use a computer-vision algorithm to automatically detect whether or not a photograph contains an animal for The Nature Conservancy to use with trail-cam footage.
Aerial images can provide useful insights into how land and waterways change over time. To be able to compare images from different sources and time periods, georeferencing (identifying the exact latitude and longitude) is required.
In partnership with the MIT Sea Grant group, students worked to automate the detection and counting of herring fish species in image and video data for efficient fishery management
As part of the Data Science for the Common Good summer program, students investigated potential issues in data-driven systems that contribute to algorithmic fairness, in order to help data practitioners understand and identify these issues in their data and the related machine learning tasks.
Associate Professor Eric Poehler of the UMass Classics department has thousands of photographic images of frescoed walls in Pompeii, the ancient city that was buried after the eruption of Mt. Vesuvius nearly 2,000 years ago. Each image has captions describing the objects included and other features. The Pompeii team will develop models to identify objects in the images, and then search images for objects that may not be mentioned in the captions. The team will also work on detecting unlabeled objects in images such as scaffolding or unwanted signage. The project results will vastly increase researchers’ ability to analyze and understand the archeology of Pompeii.