Journal and Peer-Reviewed Conference Publications:

 

1. "Biomass Estimation with GNSS Reflectometry using a Deep Learning Retrieval Model", G. Pilikos, M. P. Clarizia, N. Floury, Remote Sensing , 16(7), 1125, 2024, [doi].

 

2. "Ship Detection from raw SAR echoes using Convolutional Neural Networks", K. D. Sousa, G. Pilikos, M. Azcueta, N. Floury, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 2024, [doi].

3. "Raw SAR Data Compression with Deep Learning", G. Pilikos, M. Azcueta, R. Camarero, N. Floury, IEEE International Geoscience and Remote Sensing Symposium (IGARSS) , Athens, Greece, 2024, accepted.

 

4. "Raw Data Compression for Synthetic Aperture Radar using Deep Learning", G. Pilikos, M. Azcueta, R. Camarero, N. Floury. International Workshop on On-Board Payload Data Compression (OBPDC), Athens, Greece, 2022 [doi] [pdf].

 

5. "Single Plane-Wave Imaging using Physics-Based Deep Learning", G. Pilikos, C. L. de Korte, T. van Leeuwen, F. Lucka, IEEE International Ultrasonics Symposium, Xi'an, China, 2021 [doi] [arxiv].

 

6. "Deep Learning for Multi-View Ultrasonic Imaging Fusion", G. Pilikos, L. Horchens, T. van Leeuwen, F. Lucka, IEEE International Ultrasonics Symposium, Xi'an, China, 2021 [doi] [arxiv].

 

7. "Fast Ultrasonic Imaging using end-to-end Deep Learning", G. Pilikos, L. Horchens, K. J. Batenburg, T. van Leeuwen, F. Lucka. IEEE International Ultrasonics Symposium, Las Vegas, Nevada, USA, 2020 [doi] [arxiv].

 

8. "Deep Data Compression for Approximate Ultrasonic Image Formation", G. Pilikos, L. Horchens, K. J. Batenburg, T. van Leeuwen, F. Lucka. IEEE International Ultrasonics Symposium, Las Vegas, Nevada, USA 2020 [doi] [arxiv].

 

9. "The Relevance Vector Machine for Seismic Bayesian Compressive Sensing", G. Pilikos. GEOPHYSICS, 85 (4): WA279 - WA292, 2020 [doi] [pdf].

 

10. "Bayesian Modelling for Uncertainty Quantification in Seismic Compressive Sensing", G. Pilikos and A.C. Faul, GEOPHYSICS, 84 (2), P15 - P25, 2019 [doi] [pdf].

 

11. "Beta Process Factor Analysis for Efficient Seismic Compressive Sensing with Uncertainty Quantification", G. Pilikos and N. Philip, IEEE International Conference on Digital Signal Processing (DSP), Shanghai, China, 2018 [doi] [pdf].

 

12. "Bayesian Feature Learning for Seismic Compressive Sensing and Denoising", G. Pilikos and A. C. Faul, GEOPHYSICS, 82 (6), O91 - O104, 2017 [doi] [pdf].

 

13. "Seismic Compressive Sensing beyond aliasing using Bayesian Feature Learning", G. Pilikos, A. C. Faul and N. Philip, SEG Technical Program Expanded Abstracts 2017: pp. 4328-4332, Houston, Texas, USA, 2017 [doi].

 

14. "Relevance Vector Machines with Uncertainty Measure for Seismic Bayesian Compressive Sensing and Survey Design", G. Pilikos, A. C. Faul, IEEE International Conference on Machine Learning and Applications (ICMLA), Anaheim, California, USA, 2016 [doi] [pdf].

 

15. "The model is simple, until proven otherwise - how to cope in an ever changing world", A.C. Faul and G. Pilikos, Data for Policy, Cambridge, UK, 2016 [doi].