When computer vision works more like a brain, it sees more like people do
Training artificial neural networks with data from real brains can make computer vision more robust.
Training artificial neural networks with data from real brains can make computer vision more robust.
A new tool brings the benefits of AI programming to a much broader class of problems.
MIT researchers are discovering which parts of the brain are engaged when a person evaluates a computer program.
The MIT senior will pursue postgraduate studies in computer science in Ireland.
A new computational model could explain differences in recognizing facial emotions.
Martin Luther King Jr. Scholar bridges disciplines to translate vision into elegant math and neuroscience theory.
Professor Bilge Yildiz finds patterns in the behavior of ions across applications.
Nearly 300 government and military members participated in a new course designed to explore the next generation of artificial intelligence and related technologies.
A virtual environment embedded with knowledge of the physical world speeds up problem-solving.
Will continue initiatives in academics, mentoring, and DEIJ while building on legacy of academic and scientific excellence.
SuperUROP scholars apply deep learning to improve accuracy of climate models, profitably match computers in the cloud with customers, and more.
Her research focuses on more-efficient deep neural networks to process video, and more-efficient hardware to run applications.
Researchers propose a method for finding and fixing weaknesses in automated programming tools.
With technology new and old, instructors try to recreate the interactivity of their pre-Covid classroom.
Leveraging research done on campus, student-run MIT Driverless partners with industry collaborators to develop and test autonomous technologies in real-world racing scenarios.