The success of deep-learning models for 2D object recognition was driven in part by the availability of large-scale high-quality datasets such as ImageNet and COCO.

Bolstering the safety of self-driving cars with a deep learning-based object detection system Date: December 13, 2022 Source: Incheon National University Summary: Self-driving cars need to ...

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 ...

(Mean average precision (mAP) is a metric for evaluating object detection in deep learning.) This achievement is hugely valuable for LiDAR perception as well as 3D mapping for autonomous driving.

3D reconstruction uses an end-to-end deep learning framework that takes a single RGB color image as input and converts the 2D image to a 3D mesh model in a more desirable camera coordinate format.

Deep learning has delivered super-human accuracy for image classification, object detection, image restoration and image segmentation—even handwritten digits can be recognized.