1st MACLEAN workshop @ECML/PKDD 2019 – 20/09/2019

We are pleased to annonce that the 1st edition of MACLEAN workshop will be held in conjunction with the ECML/PKDD 2019, Wurzburg, Germany, September 20, 2019.

Website: https://mdl4eo.irstea.fr/maclean-machine-learning-for-earth-observation/

KEY DATES
Paper submission deadline (Extended): July 17th, 2019
Rejected Conference Papers sent to Workshops: July 5th, 2019
Paper acceptance notification: July 19th, 2019
Paper camera-ready deadline: July 26th, 2019
Workshop date: September 20, 2019

 

PROGRAM

10h30 – 10h40 Opening
10h40 – 11h40 Invited Speaker: Prof. Robert Jenssen
Deep learning for power line inspection

11h40 – 12h40 1st Session (3 papers): “Prediction Tasks on Earth Observation Data”
– G. Okhotnikov and N. Golyandina: EOP Time Series Prediction Using Singular Spectrum Analysis
– M. Izbicki, E. Papalexakis and V. Tsotras: The MvMF Loss for Predicting Locations on the Earth’s Surface
– C.-Y. Bai, B.-F. Chen and H.-T. Lin: Attention-based Deep Tropical Cyclone Rapid Intensification Prediction

14h00 – 15h00 Invited Speaker: Dr. Xiaoxiang Zhu
AI4EO: Artificial Intelligence in Earth Observation

15h00 – 16h00 2nd Session (3 papers): “Satellite Image Time Series Analysis”
– J. E. Gbodjo, L. Leroux, R. Gaetano and B. Ndao: RNN-based Multi-Source Land Cover mapping: An application to West African landscape
– B. Lafabregue, J. Weber, P. Gançarski and G. Forestier: Deep constrained clustering applied to remote sensing time series
– K. Reis Ferreira, L. Alves Santos and M. C. A. Picoli: Evaluating distance measures for image time series clustering in land use and cover monitoring

16h00 – 16h20 Coffee Break

16h20 – 17h00 3rd Session (2 papers): “Change Detection”
– A. Appice, N. Di Mauro, F. Lomuscio and D. Malerba: Empowering Change Vector Analysis with Autoencoding in Bi-temporal Hyperspectral Images
– A. Farasin, G. Nini, P. Garza and C. Rossi: Unsupervised Burned Area Estimation through Satellite Tiles: A multimodal approach by means of image segmentation over remote sensing imagery

17h00 – 17h15 Closing

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