Topic
Computer vision
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“Doing machine learning the right way”
Professor Aleksander Madry strives to build machine-learning models that are more reliable, understandable, and robust.
March 7, 2020 -
A new model of vision
Computer model of face processing could reveal how the brain produces richly detailed visual representations so quickly.
March 4, 2020 -
To self-drive in the snow, look under the road
Weather’s a problem for autonomous cars. MIT’s new system shows promise by using “ground-penetrating radar” instead of cameras or lasers.
February 26, 2020 -
Bridging the gap between human and machine vision
Researchers develop a more robust machine-vision architecture by studying how human vision responds to changing viewpoints of objects.
February 11, 2020 -
This object-recognition dataset stumped the world’s best computer vision models
Objects are posed in varied positions and shot at odd angles to spur new AI techniques.
December 10, 2019 -
Using computers to view the unseen
A new computational imaging method could change how we view hidden information in scenes.
December 6, 2019 -
Helping machines perceive some laws of physics
Model registers “surprise” when objects in a scene do something unexpected, which could be used to build smarter AI.
December 2, 2019 -
Predicting people's driving personalities
System from MIT CSAIL sizes up drivers as selfish or selfless. Could this help self-driving cars navigate in traffic?
November 18, 2019 -
System prevents speedy drones from crashing in unfamiliar areas
Drones can fly at high speeds to a destination while keeping safe “backup” plans if things go awry.
October 25, 2019 -
What a little more computing power can do
Commercial cloud service providers give artificial intelligence computing at MIT a boost.
September 16, 2019 -
Why did my classifier just mistake a turtle for a rifle?
Two longtime friends explore how computer vision systems go awry.
July 31, 2019 -
Teaching artificial intelligence to create visuals with more common sense
An MIT/IBM system could help artists and designers make quick tweaks to visuals while also helping researchers identify “fake” images.
July 1, 2019 -
Teaching artificial intelligence to connect senses like vision and touch
MIT CSAIL system can learn to see by touching and feel by seeing, suggesting future where robots can more easily grasp and recognize objects.
June 17, 2019 -
A 3-D printer powered by machine vision and artificial intelligence
MIT startup Inkbit is overcoming traditional constraints to 3-D printing by giving its machines “eyes and brains.”
June 4, 2019 -
For better deep neural network vision, just add feedback (loops)
The DiCarlo lab finds that a recurrent architecture helps both artificial intelligence and our brains to better identify objects.
April 29, 2019 -
Deep-learning technique reveals “invisible” objects in the dark
Method could illuminate features of biological tissues in low-exposure images.
December 12, 2018 -
Fleets of drones could aid searches for lost hikers
System allows drones to cooperatively explore terrain under thick forest canopies where GPS signals are unreliable.
November 1, 2018 -
Machines that learn language more like kids do
Computer model could improve human-machine interaction, provide insight into how children learn language.
October 31, 2018 -
Recognizing the partially seen
Advances in computer vision inspired by human physiological and anatomical constraints are improving pattern completion in machines.
September 20, 2018 -
Creating 3-D-printed “motion sculptures” from 2-D videos
CSAIL system could help athletes, dancers, and others better analyze how they move.
September 18, 2018