Directory Listing
Ali
Gurbuz
Center for Advanced Vehicular Systems
Faculty
Gurbuz
Center for Advanced Vehicular Systems
Faculty
Research Interest
Signal processing & Machine Learning
Deep learning-based Inverse Problems and Signal Processing
Computational imaging, Sparse Signal Processing, Compressive Sensing
Machine Learning for Autonomous Systems, Off-Road Autonomy
UAV based Smart Sensing Systems
Machine Learning for Radar and Remote Sensing Systems
Radar and Array Signal Processing
Deep learning-based Inverse Problems and Signal Processing
Computational imaging, Sparse Signal Processing, Compressive Sensing
Machine Learning for Autonomous Systems, Off-Road Autonomy
UAV based Smart Sensing Systems
Machine Learning for Radar and Remote Sensing Systems
Radar and Array Signal Processing
Selected Publications
Total Publications: 18
Rafi, M., Senyurek, V., & Gurbuz, A. (2024). Performance Assessment of Crop Line Detection in Corn Field from Unmanned Aerial Vehicle Video. SPIE 13053, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping IX. National Harbor, Maryland, United States: SPIE. 13053, 89-98. DOI:doi.org/10.1117/12.3013501. [Abstract] [Document Site]
Hodges, E., Chew, C., Al-Khalidi, M., Ouellette, J., Johnson, T., Lei, F., Kurum, M., Gurbuz, A., & Senyurek, V. (2024). A Blended CYGNSS Soil Moisture Product Partitioned with Ancillary Data. 2024 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM). Boulder, CO, USA: IEEE. 174. DOI:10.23919/USNC-URSINRSM60317.2024.10464722. [Abstract] [Document Site]
Bozdag, E., Nabi, M., Senyurek, V., Kurum, M., & Gurbuz, A. (2023). Fusing Sentinel-1 with CYGNSS to Account For Vegetation Effects in Soil Moisture Retrievals. IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium. Pasadena, CA: IEEE. 2693-2696. DOI:10.1109/IGARSS52108.2023.10281528. [Abstract] [Document Site]
Hicks, B., Ayna, C. O., Senyurek, V., Gupta, S., Skarke, A., & Gurbuz, A. (2023). Machine Learning Based Automated Detection of Seafloor Gas Seeps. OCEANS 2023 - MTS/IEEE U.S. Gulf Coast. Biloxi, MS, USA: IEEE. 1-6. DOI:10.23919/OCEANS52994.2023.10337038. [Abstract] [Document Site]
Nabi, M., Senyurek, V., Lei, F., Kurum, M., & Gurbuz, A. (2023). Quasi-Global Assessment of Deep Learning-Based CYGNSS Soil Moisture Retrieval. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. IEEE. 16, 5629-5644. DOI:10.1109/JSTARS.2023.3287591. [Abstract] [Document Site]
Hodges, E., Chew, C., Al-Khalidi, M., Ouellette, J., Johnson, T., Lei, F., Kurum, M., Gurbuz, A., & Senyurek, V. (2024). A Blended CYGNSS Soil Moisture Product Partitioned with Ancillary Data. 2024 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM). Boulder, CO, USA: IEEE. 174. DOI:10.23919/USNC-URSINRSM60317.2024.10464722. [Abstract] [Document Site]
Bozdag, E., Nabi, M., Senyurek, V., Kurum, M., & Gurbuz, A. (2023). Fusing Sentinel-1 with CYGNSS to Account For Vegetation Effects in Soil Moisture Retrievals. IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium. Pasadena, CA: IEEE. 2693-2696. DOI:10.1109/IGARSS52108.2023.10281528. [Abstract] [Document Site]
Hicks, B., Ayna, C. O., Senyurek, V., Gupta, S., Skarke, A., & Gurbuz, A. (2023). Machine Learning Based Automated Detection of Seafloor Gas Seeps. OCEANS 2023 - MTS/IEEE U.S. Gulf Coast. Biloxi, MS, USA: IEEE. 1-6. DOI:10.23919/OCEANS52994.2023.10337038. [Abstract] [Document Site]
Nabi, M., Senyurek, V., Lei, F., Kurum, M., & Gurbuz, A. (2023). Quasi-Global Assessment of Deep Learning-Based CYGNSS Soil Moisture Retrieval. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. IEEE. 16, 5629-5644. DOI:10.1109/JSTARS.2023.3287591. [Abstract] [Document Site]