Researchers have adapted deep learning techniques in a multi-object tracking framework, overcoming short-term occlusion and achieving remarkable performance without sacrificing computational speed.

The 4D tracking techniques would use 4D dynamic solid modeling of a cluttered space by collecting depth data from 3D cameras. These modeling concepts can then be applied in a number of use cases.

Future integration of the deep learning algorithm into standard system software would allow factory engineers to train networks that could then be run locally for inspection. There are many more ...

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 ...

Shenzhen Huayan Intelligent Co., Ltd. applied for a patent titled "Robot Control Method for Object Surface Tracking and Related Equipment" in June 2025, which was officially published on August 27.

[Anton] developed this real-time tracking tool for deep sky objects (DSOs) to keep tabs on most of the interesting things out there a telescope can be pointed at.

The innovations address multi-object tracking, a process used by robotic systems to track the position and motion of objects – including vehicles, pedestrians and cyclists – to plan the path of ...

The MIT researchers now plan to develop deep neural networks that mimic other visual processing systems, such as motion tracking and recognizing three-dimensional forms.