With programmable pixels, novel sensor improves imaging of neural activity
New camera chip design allows for optimizing each pixel’s timing to maximize signal-to-noise ratio when tracking real-time visual indicator of neural voltage.
New camera chip design allows for optimizing each pixel’s timing to maximize signal-to-noise ratio when tracking real-time visual indicator of neural voltage.
DenseAV, developed at MIT, learns to parse and understand the meaning of language just by watching videos of people talking, with potential applications in multimedia search, language learning, and robotics.
The technique characterizes a material’s electronic properties 85 times faster than conventional methods.
“Alchemist” system adjusts the material attributes of specific objects within images to potentially modify video game models to fit different environments, fine-tune VFX, and diversify robotic training.
For the first time, researchers use a combination of MEG and fMRI to map the spatio-temporal human brain dynamics of a visual image being recognized.
By providing plausible label maps for one medical image, the Tyche machine-learning model could help clinicians and researchers capture crucial information.
FeatUp, developed by MIT CSAIL researchers, boosts the resolution of any deep network or visual foundation for computer vision systems.
The sticky, wearable sensor could help identify early signs of acute liver failure.
Cancer nanomedicine was on display at the 2023 White House Demo Day.
MIT professor combines nanoscience and viruses to develop solutions in energy, environment, and medicine.
The neuroscientist is recognized for her ongoing work to understand molecular and cellular mechanisms that enable the brain to adapt to experience.
Using fluorescent labels that switch on and off, MIT engineers can study how molecules in a cell interact to control the cell’s behavior.
The wearable device, designed to monitor bladder and kidney health, could be adapted for earlier diagnosis of cancers deep within the body.
A pivotal talk led postdoc Kristina Monakhova to develop smart, computational cameras and microscopes for intelligent systems.
MIT CSAIL researchers combine AI and electron microscopy to expedite detailed brain network mapping, aiming to enhance connectomics research and clinical pathology.