IMAGE RECOGNITION AND CLASSIFICATION ALGORITHMS BASED ON ARTIFICIAL NEURAL NETWORKS

In recent years, image recognition and classification have emerged as critical tasks in artificial intelligence, driven by rapid advancements in artificial neural networks (ANNs). This paper explores the application of deep learning architectures, especially Convolutional Neural Networks (CNNs), in image processing. The research highlights the key algorithms, evaluates their accuracy, efficiency, and applicability across different datasets, and compares their performance metrics. Through analytical tables and discussions, the paper reveals how neural networks outperform traditional approaches in recognizing and classifying complex image patterns.