Synergizing AI for Cognitive Insights, Visual Pattern Recognition, and Computational Advancements: A Novel Exploration of EEG Detection, Deep Learning, and Cat Swarm Optimization

Abstract

AI integration with cognitive science helps scientists develop better methods to read brain activity signals and recognize visual patterns plus optimize computing tasks. Our study develops a new cognitive approach which integrates deep learning algorithms with both visual pattern recognition and cat swarm optimization to improve data analysis speeds. The suggested framework joins different fields to combat EEG noise issues and fix issues with standard pattern recognition and suboptimal optimization solutions. The study tests this method's success in healthcare services and shows its benefits for computer thinking and robot applications.