Mineral Data

Mineral data analysis is undergoing a transformation driven by advancements in machine learning and remote sensing technologies. Current research focuses on developing and applying deep learning models, such as convolutional neural networks and YOLO-based architectures, to improve the efficiency and accuracy of mineral identification, classification, and prospectivity mapping from diverse data sources including hyperspectral imagery, UAV-acquired data, and measurement-while-drilling information. These improvements are crucial for optimizing mineral exploration, resource extraction, and ultimately, reducing the environmental and economic costs associated with mining operations.