In recent years, advancements in sustainable intelligent transportation have emphasized the
significance of vehicle detection and tracking for real-time traffic flow management on the …

The carbon budget has emerged as a central focus in global carbon cycle research. The
limited understanding of carbon budget balance dynamics has led to an increasing …

One fascinating aspect of pre-trained vision-language models~(VLMs) learning under
language supervision is their impressive zero-shot generalization capability. However, this …

Auction-based incentive mechanisms can satisfy the heterogeneous demands of both
Demand Side Platforms (DSP) and Supply Side Platforms (SSP) in Internet of Things (IoT) …

Vision-centric perception systems for autonomous driving have gained considerable
attention recently due to their cost-effectiveness and scalability especially compared to …

The visual path–following technology is widely used in cutting, laser welding, painting,
gluing, and other fields, which is a crucial content of robotics studies. As an important …

Video game development is getting increasingly effective as AI paradigms advance. Deep
Reinforcement Learning (DRL) is a promising artificial intelligence (AI) approach. It …

Deep reinforcement learning (DRL) is a primary machine learning approach for solving
sequential decision problems. To exploit the potential vulnerabilities of DRL, we propose a …

The dwell-time algorithm is one of the critical technologies in magnetorheological finishing,
and its solution accuracy largely determines the final processing quality. In this study, the …

This paper investigates the multi-agent interception problem under switching topology
based on deep reinforcement learning. Due to communication restrictions or network …