- Koch, A., Petry, M., Ghiglione, M., Raoofy, A., Dax, G., Furano, G., Werner, M., Trinitis, C., & Langer, M. (2023). Machine Learning Application Benchmark (accepted). Proceedings of the 20th ACM International Conference on Computing Frontiers. [BibTeX]
- Li, H., Yuan, Z., Dax, G., Gong, K., Fan, H., Zipf, A., & Werner, M. (2023). Semi-supervised Learning from Street-View Images and OpenStreetMap for Automatic Building Height Estimation (accepted). GIScience 2023. [BibTeX]
- Dong, Z., Xiong, Z., Dax, G., Li, H., Langer, M., Ghiglione, M., Trinitis, C., & Werner, M. (2023). Forest Fire Detection from Sentinel-2 Satellite Imagery using Deep Learning (accepted). Big Earth Data. [BibTeX]
- Dax, G., Nagarajan, S., Li, H., & Werner, M. (2023). Compression Supports Spatial Deep Learning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 16, 702–713. https://doi.org/10.1109/JSTARS.2022.3226563 [doi] [BibTeX]
- Denizoglu, D. G., Dax, G., Nagarajan, S., Zhang, N., & Werner, M. (2022). Global Active Fire Detection – Towards a SAR-enabled Multi-Sensor Global Monitoring System. Living Planet Symposium 2022. [PDF] [BibTeX]
- Raoofy, A., Dax, G., Serra, V., Ghiglione, M., Werner, M., & Trinitis, C. (2022). Benchmarking and feasibility aspects of machine learning in space systems. Proceedings of the 19th ACM International Conference on Computing Frontiers, 225–226. https://doi.org/10.1145/3528416.3530986 [PDF] [doi] [BibTeX]
- Ghiglione, M., Serra, V., Raoofy, A., Dax, G., Trinitis, C., Werner, M., Schulz, M., & Furano, G. (2022). Survey of frameworks for inference of neural networks in space data system. DASIA 2022. [PDF] [BibTeX]
- Dax, G., & Werner, M. (2022). The Role of Compression in Spatial Computing. PhD Colloquium of the DGK Section on Geoinformatics 2022. [PDF] [Online] [BibTeX]
- Dax, G., & Werner, M. (2021). Trajectory Similarity using Compression. 2021 22nd IEEE International Conference on Mobile Data Management (MDM), 169–174. https://doi.org/10.1109/MDM52706.2021.00035 [PDF] [doi] [BibTeX]
- Ghiglione, M., Raoofy, A., Dax, G., Furano, G., Wiest, R., Trinitis, C., Werner, M., Schulz, M., & Langer, M. (2021). Machine Learning Application Benchmark for Satellite On-Board Data Processing. In European Workshop on On-Board Data Processing. https://doi.org/10.5281/zenodo.5520877 [PDF] [doi] [BibTeX]
- Raoofy, A., Dax, G., Ghiglione, M., Langer, M., Trinitis, C., Werner, M., & Schulz, M. (2021). Benchmarking Machine Learning Inference in FPGA-based Accelerated Space Applications. Workshop on Benchmarking Machine Learning Workloads on Emerging Hardware. [PDF] [BibTeX]
- Alam, S., Ahmed, M., Dax, G., & Werner, M. (2021). Change detection of Lake Starnberg, Germany using NDVI and Sentinel 2. Symposium Für Angewandte Geoinformatik (AGIT’2021). [PDF] [BibTeX]
- Zeya, S. M., Theofanidis, A., Dax, G., & Werner, M. (2021). Forest and Vegetation Monitoring Using Sentinel-2 Imageryin the Northern Part of Democratic Republic of Congo. Proceedings of the 24th AGILE Conference on Geographic Information Science (AGILE’2021). [PDF] [BibTeX]
- Dax, G., & Werner, M. (2021). Information-optimal Abstaining for Reliable Classification of Building Functions. AGILE: GIScience Series, 2, 1–10. https://doi.org/10.5194/agile-giss-2-1-2021 [PDF] [doi] [BibTeX]
- Dax, G., Laass, M., & Werner, M. (2021). Genetic Algorithm for Improved Transfer Learning Through Bagging Color-Adjusted Models. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2612–2615. https://doi.org/10.1109/IGARSS47720.2021.9554380 [PDF] [doi] [BibTeX]
- Götzer, S., Laass, M., Dax, G., & Werner, M. (2021). ObservaToriUM: A Simple Scalable Earth Observation Processing Engine. Symposium Für Angewandte Geoinformatik (AGIT’2021). [PDF] [BibTeX]
- Werner, M., Dax, G., & Laass, M. (2020). Computational Challenges for Artificial Intelligence and Machine Learning in Environmental Research. INFORMATIK 2020. https://doi.org/10.18420/inf2020_95 [doi] [BibTeX]
- Dumitru, C. O., Schwarz, G., Ao, D., Dax, G., Karmakar, C., & Datcu, M. (2020). Selection of Reliable Machine Learning Algorithms for Geophysical Applications. EGU 2020. https://elib.dlr.de/138129/ [Online] [BibTeX]
- Dumitru, C. O., Schwarz, G., Dax, G., Vlad, A., Ao, D., & Datcu, M. (2020). Active and Machine Learning for Earth Observation Image Analysis with Traditional and Innovative Approaches. In H. R. Arabnia, K. Daimi, R. Stahlbock, C. Soviany, L. Heilig, & K. Brussau (Eds.), Principles of Data Science (pp. 207–231). Springer Nature Switzerland AG. https://elib.dlr.de/138139/ [Online] [BibTeX]
- Coca, M., Datcu, M., Dax, G., Dumitru, C. O., Schwarz, G., & Yao, W. (2019, September). No Feature Data Analytics: Compression Pattern Recognition. Φ-Week. https://elib.dlr.de/130276/ [Online] [BibTeX]
- Dax, G., Dumitru, C. O., Schwarz, G., & Datcu, M. (2019). SAR Change Detection in a General Case Using Normalized Compression Distance. TerraSAR-X Science Team Meeting 2019. https://elib.dlr.de/130271/ [Online] [BibTeX]
- Dumitru, C. O., Dax, G., Schwarz, G., Cazacu, C., Adamescu, M. C., & Datcu, M. (2019). Accurate Monitoring of the Danube Delta Dynamics using Copernicus Data. SPIE Remote Sensing, 1–13. https://elib.dlr.de/129121/ [Online] [BibTeX]