Nature

Deep reinforcement learning for scheduling semiconductor cluster tools in varying configurations

The growing importance of semiconductor productivity is driving a critical need for optimization in manufacturing. As the semiconductor industry continues to transition to smaller process nodes, such ...
Nature

Dense extreme inception network-based edge detection with deep reinforcement learning for object localization in an underwater environment

The underwater environment is characterized by the vast expanses of water bodies such as seas, oceans, rivers, and lakes, together with their related ecosystems, that exist under the Earth’s surface.
Frontiers

Renewable Energy and Artificial Intelligence in Urban Agriculture: Pathfinding Smart and Sustainable Food Systems

By 2050, urban centers will house nearly 70% of the global population. Transitioning to localized food production via Urban Agriculture (UA) including ...
Scientific Research Publishing

Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features ()

Phishing is a form of cybercrime in which people are deceived into exposing their personal information which can result in ...