Abstract Nowadays, Multi Robotic System (MRS) consisting of different robot shapes, sizes
and capabilities has received significant attention from researchers and are being deployed …

The building and construction industry has consistently been a major contributor to energy
consumption and carbon emissions. With stochastic interactions between occupants and …

In recent years, reinforcement learning and bandits have transformed a wide range of real-
world applications including healthcare, finance, recommendation systems, robotics, and …

Deep Generative AI has been a long-standing essential topic in the machine learning
community, which can impact a number of application areas like text generation and …

Vision transformers (ViTs) are increasingly utilized for HSI classification due to their
outstanding performance. However, ViTs encounter challenges in capturing global …

We propose a model-free deep reinforcement learning method for controlling the
synchronization between two identical chaotic systems, one target and one reference. By …

Abstract Temporal Action Detection (TAD) aims to accurately capture each action interval in
an untrimmed video and to understand human actions. This paper comprehensively surveys …

Artificial intelligence has made remarkable progress in handling complex tasks, thanks to
advances in hardware acceleration and machine learning algorithms. However, to acquire …

Bundle adjustment is the common way to solve localization and mapping. It is an iterative
process in which a system of non-linear equations is solved using two optimization methods …

It is well-known that image quality assessment usually meets with the problem of perception-
distortion (pd) tradeoff. The existing deep image super-resolution (SR) methods either focus …