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

Geopolitics, History, and International Relations, Vol. 15, No. 2 (2023), pp. 39-53 (15 pages) Based on an in-depth survey of the literature, the purpose of the paper is to explore urban modeling and ...

Researchers have developed a new high-speed way to detect the location, size and category of multiple objects without acquiring images or requiring complex scene reconstruction. Because the new ...

Scientists at Brigham Young University (BYU) have developed an algorithm that can accurately identify objects in images or videos and can learn to recognize new objects on its own. Although other ...