Adaptive Structure

Adaptive structure research focuses on creating systems and algorithms that dynamically adjust their configuration or behavior in response to changing conditions or tasks. Current efforts concentrate on developing novel neural network architectures, such as those employing adaptive activation functions and dynamically evolving topologies, and on improving the robustness and efficiency of structure-from-motion algorithms through techniques like coarse-to-fine refinement and federated learning. These advancements have significant implications for various fields, including structural health monitoring, robotics, and machine learning, by enabling more efficient, robust, and adaptable systems.