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 ...

The method can be applied to autonomous vehicles, autonomous parking, autonomous delivery, and future autonomous robots as well as in applications where object and obstacle detection, tracking ...

Real-world vision systems rely on 3D object detection, which is critical in developing perception capabilities for AVs and mobile autonomous robots. But what’s the best approach ...

Three-dimensional object detection is crucial for autonomous vehicles. It utilizes point cloud data generated by LiDAR to help autonomous vehicles identify surrounding objects. This technology is ...

The autonomy revolution is progressing. Helm.ai's unsupervised learning and generative AI approach offers scalability, deployment speed and resource efficiency.

An Israeli artificial intelligence startup gets $12.5 million in funding for a deep learning processor they plan to apply to autonomous vehicles.

Apple researchers are pushing forward with efforts to bring autonomous vehicle systems to public roads, and last week published an academic paper outlining a method of detecting objects in 3D ...

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.