Welcome to the Cloud Detection Challenge, hosted by IEEE MetroXRAINE 2024!

In this competition, researchers worldwide are invited to tackle the task of binary classification focused on cloud detection using a novel dataset exclusively released for this challenge. The dataset has been meticulously constructed by transforming raw data collected by a measuring instrument, specifically a lidar-based ceilometer, into images. These images are not conventional photographs of the sky or satellite images but are generated using backscatter profile measurements that depict the evolution of the sky's state above the instrument. Images were generated daily and subsequently divided into hourly segments.

The objective is to develop innovative solutions or architectures that surpass the proposed baseline, achieving higher accuracy in cloud detection. Participants will be provided with a dataset of images, each labelled with binary annotations indicating the presence or absence of clouds. The challenge is to design and implement a classification model that accurately identifies cloud presence in these images. The dataset is diverse, encompassing various environmental conditions, perspectives, and challenges commonly encountered in real-world scenarios.

The performance of the models will be evaluated based on accuracy, F1 score, precision, and recall, emphasizing achieving superior results compared to the baseline model provided. All metrics will be considered, and the winner will be the team with the best overall performance across all metrics. In case of a tie, precision and recall values will be prioritized. If a further tie occurs, the solution with the highest accuracy value will be selected. The evaluation order is as follows: (1) F1 score, (2) precision and recall, (3) accuracy.

The baseline model will serve as a carefully crafted reference point for participants to surpass. The goal is to showcase advancements in cloud detection through cutting-edge techniques, novel architectures, or innovative pre-processing methods.

Organizers And Contacts

• Alessio Barbaro Chisari, Ph.D Student, Università degli Studi di Catania, Italy
• Sebastiano Battiato (Ph.D.), Full Professor, Università degli Studi di Catania, Italy
• Luca Guarnera (Ph.D.), Fellow Researcher, Università degli Studi di Catania, Italy
• Alessandro Ortis (Ph.D.), Fellow Researcher, Università degli Studi di Catania, Italy
• Wladimiro Carlo Patatu, R&D Manager and Domain Expert, EHT S.C.p.A., Italy
• Mario Valerio Giuffrida (Ph.D.), Assistant Professor, University of Nottingham, United Kingdom

Further information

Learn more about the organization of the challenge.

Training Set Now Available!

You can download the training set here.

Test Set Now Available!

The link to download the test set was sent to registered teams by email. You can download it here. For any needs, please contact us. Please, submit your solution using this form.