A team of computer scientists at the University of Massachusetts Amherst working on two different problems—how to quickly detect damaged buildings in crisis zones and how to accurately estimate the size of bird flocks—recently .
A team of computer scientists at the University of Massachusetts Amherst working on two different problems—how to quickly detect damaged buildings in crisis zones and how to accurately estimate the size of bird flocks—recently announced an AI framework that can do both. The framework, called DISCount, blends the speed and massive data-crunching power of artificial intelligence with the reliability of human analysis to quickly deliver reliable estimates that can quickly pinpoint and count specific features from very large collections of images.
The research, published in Proceedings of the AAAI Conference on Artificial Intelligence, has been recognized by that association with an award for the best paper on AI for social impact.
«DISCount came together as two very different applications,» says Subhransu Maji, associate professor of information and computer sciences at UMass Amherst and one of the paper’s authors. «Through UMass Amherst’s Center for Data Science, we have been working with the Red Cross for years in helping them to build a computer vision tool that could accurately count buildings damaged during events like earthquakes or wars.
