A Comprehensive Overview of Artificial Neural Networks: Evolution, Architectures, and Applications

Abstract

Artificial Neural Networks (ANNs) have emerged as powerful computational models
inspired by biological neural networks. This paper provides a comprehensive overview of ANNs,
covering their evolutionary development, diverse architectures ranging from feedforward to
recurrent and convolutional networks, and their wide-ranging applications across various domains.
The abstract emphasizes their transformative impact on machine learning and artificial
intelligence