Bolstering the safety of self-driving cars with a deep learning-based object detection system. ScienceDaily . Retrieved May 13, 2025 from www.sciencedaily.com / releases / 2022 / 12 / 221212140800.htm ...

Autonomous vehicles require object detection systems to navigate traffic and avoid obstacles on the road. However, current detection methods often suffer from diminished detection capabilities due ...

A new data-driven technique for obstacle avoidance in autonomous vehicles is reported in the International Journal of Vehicle ...

Object detection is used in many different domains, including autonomous driving, video surveillance, and healthcare. In this post, I will briefly review the deep learning architectures that help ...

Instead of tricking an autonomous vehicle into avoiding a perceived object, these attacks aim to block object detection entirely. The consequences of this aren't hard to imagine.

Traditional approaches to autonomous vehicles (AVs) rely on using millions of miles of driving data in conjunction with even more miles of simulated data as inputs to supervised machine learning ...

3D object detection (3DOD) is central to real-world vision systems and a critical component in the development of perception capabilities for autonomous vehicles (AVs) and mobile autonomous robots.

Real 'autonomous' vehicles rely on a diverse array of sensors capable of 'superhuman' object detection. It’s not perfect.