Certified AI at the Edge: What the WCET-CAN Theorem Means for AI in Regulated Industries

And without that proof, no safety-critical system can be certified with a neural network in its control loop. A new theorem ...

Ukraine's defence ministry explains how AI-enabled drones are disrupting Russian logistics

Artificial intelligence is being integrated into Ukrainian mid-range drones used by Ukrainian forces to strike Russian ...

The Tesla Model Y's "supervised" full self-driving (FSD) mode blew me away

The Tesla Model Y's (Supervised) Full Self-Driving (FSD) Mode Blew Me Away ...
MSN on MSN

Move over, NASA, this Jharkhand AI breakthrough could guide future space missions

At BIT Mesra in Ranchi, a three-woman team has trained AI to detect and analyse lunar craters. The ISRO-backed work could ...
WLRN

In the brain, objects seen and imagined follow the same neural path

It's often called the mind's eye. "I can look at an object in the world around me, but I can also close my eyes and imagine the object," says Varun Wadia, a brain scientist at Cedars-Sinai Medical ...
Nature

Pseudo-depth-based deep neural network model for object detection

Current machine learning methods only utilize the three-channel color features of optical images for computer visual tasks. However, the optical images only explicitly present information of RGB color ...
IEEE

Object Detection with Spiking Neural Networks on Event Videos for Driving Scenarios

Abstract: Event cameras excel in imaging objects under challenging lighting conditions with low latency. Their sparse and asynchronous event outputs closely align with the operational paradigm of ...
eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Remarkably, human brains have the ability to accurately perceive and process the real-world size of objects, despite vast differences in distance and perspective. While previous studies have delved ...
Nature

Pedestrian detection in aerial image based on convolutional neural network with attention mechanism and multi-scale prediction

Pedestrian object detection is crucial in intelligent systems such as traffic management and surveillance. Traditional machine learning methods have shown drawbacks, including low accuracy and slow ...
Frontiers

A vision-based drowsiness detection system for railway operators using lightweight convolutional neural networks

This research addresses the challenge of monitoring railway driver drowsiness using a real-time, vision-based system powered by convolutional neural networks, specifically the YOLOv8 architecture ...
Scientific Research Publishing

Srivastava, U.C., et al. (2020) Intracranial Hemorrhage Detection Using Neural Network Based Methods with Federated Learning.

ABSTRACT: Intracranial hemorrhage (ICH) is a critical subtype of stroke that arises from bleeding within the brain and often leads to severe neurological damage or death if not diagnosed at an early ...