Feature Extraction
Feature Extraction in Convolutional Neural Networks refers to the process of deriving high-level, meaningful representations from raw data. It involves identifying and isolating relevant features from input images, enabling the network to recognize patterns and make predictions based on those features. In the context of Technology, Artificial Intelligence, and Deep Learning, Feature Extraction plays a crucial role in optimizing model performance by reducing dimensionality while preserving essential information. By focusing on pertinent characteristics, this process enhances the overall efficiency and accuracy of Convolutional Neural Networks across various applications.