IEEE Access

Great news! The paper Cloud Detection Challenge – Methods and Results has been accepted for publication in IEEE Access (Q1, I.F. 3.4)

This work presents the Cloud Detection Challenge, an initiative aimed at improving cloud detection using LiDAR-based ceilometer data. We introduced a novel dataset of backscatter profiles transformed into time-height plots, providing a benchmark for state-of-the-art deep learning models. The challenge attracted teams from around the world, who developed AI-based solutions, including CNNs and Transformers, to push the limits of cloud detection technology.

Authors: Alessio Chisari, Luca Guarnera, Alessandro Ortis, Wladimiro Carlo Patatu, Bruno Casella, Luca Naso, Giuseppe Puglisi, Vincenzo Del Zoppo, Mario Valerio Giuffrida, Sebastiano Battiato

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