Classical Neural Network

Classical neural networks are computational models inspired by the structure and function of biological neural systems, primarily aimed at learning complex patterns from data. Current research emphasizes improving their efficiency, robustness, and interpretability, exploring architectures like convolutional and graph neural networks, as well as hybrid models integrating classical networks with quantum computing approaches. These advancements are driving progress in diverse fields, including medical image analysis, power flow analysis, and natural language processing, by enabling more accurate, efficient, and explainable solutions to complex problems.