Noncooperative target detection in real-world scenarios relies on large-scale deep neural networks after image capture. However, directly implementing this detection pipeline under conventional ...

American streets are incredibly dangerous for pedestrians. A San Carlos, California-based startup called Obvio thinks it can change that by installing cameras at stop signs -- a solution the ...

We report a semi-supervised Vision Transformer (ViT) framework for automated reflection high energy electron diffraction (RHEED) image classification of ferroelectric nitride (ScAlN) materials grown ...

Lane-keeping systems are a major part of advanced driver assistance systems (ADAS). Existing lane detection algorithms are based on either Computer Vision (CV) models or deep learning techniques which ...

This project explores the integration of YOLO (You Only Look Once) and Graph Neural Networks (GNNs) for traffic sign detection and graph-based relationship modeling. While YOLO efficiently detects and ...

Traffic signs recognition (TSR) is an important part of some advanced driver-assistance systems (ADASs) and auto driving systems (ADSs). As the first key step of TSR, traffic sign detection (TSD) is a ...

DJI Automotive’s take on the vision-based approach is apparently more concise than Tesla’s FSD, omitting even the ultrasonic sensors. The company was ostensibly the first to consider replacing LiDAR ...

This paper presents the implementation of an embedded automotive system that detects and recognizes traffic signs within a video stream. In addition, it discusses the recent advances in driver ...