About
Sebastiano Serpico is a Professor at the Department of Naval, Electrical, Electronic and Telecommunications Engineering (DITEN) of the University of Genoa, Italy, and serves as President of the university's Scuola Superiore IANUA graduate school.
His research centers on remote sensing image analysis, specializing in machine learning and deep learning techniques for image classification, semantic segmentation, and change detection. He integrates convolutional neural networks with probabilistic graphical models (Markov Random Fields, Conditional Random Fields) to process multi-sensor and multi-resolution data from satellites and UAVs, with strong emphasis on environmental monitoring applications.
Recent publications reveal a dominant focus on fusing hyperspectral, SAR, and optical data using deep learning architectures for natural disaster management and water-related risk assessment. His work demonstrates consistent innovation in multiresolution fusion frameworks and unsupervised feature extraction, particularly addressing challenges in heterogeneous data analysis for environmental risk programs like Italy's 'Return' initiative under the EU Next Generation framework.
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