Modern smartphones are packed with incredible technology, from high-resolution cameras and advanced graphics chips to AI processors. In premium models, this hardware includes LiDAR (light detection ...

The following figure outlines the high level structure of the algorithm, which covers the tasks of multi-modal sensor fusion and object tracking. The algorithm is developed for the Indy Autonomous ...

Project is meant to provide a simple yet powerful baseline for multiple object tracking without the hassle of writing the obvious algorithm stack yourself. - tracking by detection paradigm - IOU + ...

Abstract: Aiming at the problem that the multi-object tracking algorithm is difficult to accurately design the object feature model and data association algorithm in the process of unmanned vehicle ...

This article presents a novel target tracking algorithm for hyperspectral low altitude UAV, combining deep learning with an improved Kernelized Correlation Filter (KCF). Initially, an image noise ...

A team has shown that reinforcement learning -i.e., a neural network that learns the best action to perform at each moment based on a series of rewards- allows autonomous vehicles and underwater ...

Abstract: Most tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework called Hidden Markov Model, where the distribution of the object state at current ...

The University of Glasgow has worked with Fujitsu and satellite service and sustainability firm Astroscale on a quantum-inspired project to remove space debris. The project, carried out as part of the ...