Deep learning techniques have transformed the analysis of vast amounts of visual data, creating significant opportunities in cultural heritage. Advanced machine learning models can enhance the understanding of artworks, historical artifacts, and archaeological findings. By automating tasks such as image recognition, feature extraction, and pattern analysis, these technologies help researchers uncover details and relationships that would otherwise remain hidden, there by advancing scholarly research and heritage preservation. This research project focuses on applying deep learning to the study of cultural, historical, and artistic heritage. By utilizing advanced machine learning methods for image recognition and interpretation, it aims to analyze various forms of visual data, from artworks to archaeological artifacts. The project seeks to develop automated tools for extracting meaningful insights, facilitating a deeper understanding of their artistic, historical, and cultural significance.
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[Website Università degli Studi di Milano]