Francesco Ciccone is a PhD candidate in Aerospace Science and Technology (DAST), currently working on environmental monitoring and the prevention of critical or at-risk events through the use of Artificial Intelligence models for processing aerial images. His research focuses on the application of Deep Learning-based Computer Vision models for the early detection of fires and hydrogeological disruptions from aircraft. His activities include the development of object detection models for searching for missing people, the segmentation of landslides from aerial images for the assessment of damage caused by environmental disasters, and the design of innovative models of convolutional neural networks for GPS image-based applications. His experience and publications also demonstrate a constant commitment to applying Artificial Intelligence to the optimization of production processes, with particular attention to Additive Manufacturing.
