Deep Learning Approaches for Fine Art Painting Classification

research project about painting classification in the fine arts domain. The study focused on the challenges of classifying artworks due to variations in artistic styles and techniques. I explored traditional methods versus deep learning approaches, and evaluated the performance of three deep learning models. In particular, I tested YOLO, known for real-time detection, and VGG16, recognized for feature extraction. The research aimed to improve both accuracy and efficiency in fine art classification.