It’s this or the doctor needs to practice good penmanship…
The feature can detect medications in hastily scrawled scripts.
Category: robotics/AI – Page 1,472
A digital spinal cord that streams your thoughts | Thomas Oxley | TEDxSydney
In what could be the first direct link between AI and the human brain, interventional neurologist Thomas Oxley reveals the world’s first minimally invasive digital spinal cord. He shares the exciting story behind the ongoing development of this unique wireless device that can interpret signals from the brain for patients with paralysis without the need for open brain surgery or direct contact with brain tissue. Endovascular neurologist Thomas Oxley’s 2016 research demonstrated the potential for a neural recording device to be engineered onto a stent and implanted into a blood vessel in the brain, without the need for open brain surgery.
This research has progressively attracted investment, with completion of a Series A fundraiser in 2017. His company’s technology, the Stentrode, currently under FDA review, is planned for a first in human trial. Patients with tetraplegia due to spinal cord injury, stroke and ALS will be recruited into a trial of direct brain control over a suite of assistive technologies. This talk was given at a TEDx event using the TED conference format but independently organized by a local community.
AI Explains: Humans
Today we take a deep dive into the fascinating species that is Homo Sapiens.
AI Helped Find Over 50,000 Years Old Hybrid Human Ancestor
As they suggest, Denisova 11 was not an isolated case but rather a hint of a more general introgression process.
This study was the first to use deep learning technologies to inspect human evolution. In the future, it’s expected to become more common in fields such as biology, genomics and evolution.
A face recognition framework based on vision transformers
Face recognition tools are computational models that can identify specific people in images, as well as CCTV or video footage. These tools are already being used in a wide range of real-world settings, for instance aiding law enforcement and border control agents in their criminal investigations and surveillance efforts, and for authentication and biometric applications. While most existing models perform remarkably well, there may still be much room for improvement.
Researchers at Queen Mary University of London have recently created a new and promising architecture for face recognition. This architecture, presented in a paper pre-published on arXiv, is based on a strategy to extract facial features from images that differs from most of those proposed so far.
“Holistic methods using convolutional neural networks (CNNs) and margin-based losses have dominated research on face recognition,” Zhonglin Sun and Georgios Tzimiropoulos, the two researchers who carried out the study, told TechXplore.