MIT researchers combine deep learning and physics to fix motion-corrupted MRI scans
The challenge involves than just a blurry JPEG. Fixing motion artifacts in medical imaging requires a more sophisticated approach.
computer-vision
Using AI to protect against AI image manipulation
“PhotoGuard,” developed by MIT CSAIL researchers, prevents unauthorized image manipulation, safeguarding authenticity in the era of advanced generative models.
A new dataset of Arctic images will spur artificial intelligence research
The dataset, being collected as part of a US Coast Guard science mission, will be released open source to help advance naval mission planning and climate change studies.
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.
Computer vision system marries image recognition and generation
MAGE merges the two key tasks of image generation and recognition, typically trained separately, into a single system.
Researchers use AI to identify similar materials in images
This machine-learning method could assist with robotic scene understanding, image editing, or online recommendation systems.
Using reflections to see the world from new points of view
A new computer vision system turns any shiny object into a camera of sorts, enabling an observer to see around corners or beyond obstructions.
Training machines to learn more like humans do
Researchers identify a property that helps computer vision models learn to represent the visual world in a more stable, predictable way.
Deep-learning system explores materials’ interiors from the outside
A new method could provide detailed information about internal structures, voids, and cracks, based solely on data about exterior conditions.
Making property assessments as simple as snapping a picture
The technology of MIT alumni-founded Hosta a.i. creates detailed property assessments from photos.