Object detection in deep learning encompasses a range of approaches that identify and localise instances of semantic classes in images. Early methods relied on two-stage architectures, first ...

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 to ...

The novel technique is based on the VarifocalNet deep-learning object detection framework, which was reportedly tweaked to achieve quicker and more accurate results. Compared to other such methods, ...

Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning algorithms, ClairS-TO and Clair3-RNA, that significantly advance genetic ...

LINCOLNSHIRE, Ill.--(BUSINESS WIRE)-- Zebra Technologies Corporation (NASDAQ: ZBRA), a leading digital solution provider enabling businesses to intelligently connect data, assets, and people, today ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

A new object detection system utilizes the state-of-the-art YOLOv3 (You Only Look Once) algorithm, offering significantly improved detection capabilities even under unfavorable conditions and can, ...