TH-A3.1P.5
Ground Moving Target Detection Using Geometric Feature Based Machine Learning Classifier
Rafi Ahmed, Florida International University, United States; Hai Deng, Nanjing University of Aeronautics and Astronautics, China
Session:
Microwave Remote Sensing Oral
Track:
AP-S: Track 3: Propagation and Scattering
Location:
Room 251C
Session Time:
Thu, 16 Jul, 15:20 - 17:00
Presentation Time:
Thu, 16 Jul, 16:40 - 17:00
Presentation
Discussion
Session TH-A3.1P
TH-A3.1P.1: Digital Elevation Model from UAS-SAR single-pass interferometry
Alessandra Beni, Lapo Miccinesi, Andrea Cioncolini, Luca Bigazzi, Lorenzo Pagnini, Andrea Bulletti, Paolo Mazzanti, Massimiliano Pieraccini, University of Florence, Italy
TH-A3.1P.2: Research on Snow Depth Estimation Method Based on a Convolution-Transformer Hybrid Network
shilei liu, Central South University, China; Yanting Zhou, China Academy of Space Technology, China; mingjun li, Chengwang Xiao, Jian Dong, Central South University, China
TH-A3.1P.3: Arctic Sea Ice Snow Thickness Inversion Using Multi-Layer Feedforward Neural Network with Multi polarized SMOS brightness temperature Data
Chengwang Xiao, Jinyuan Tian, Central South University, China; Haofeng Dou, the China Academy of Space Technology (Xi’an), China; Jian Dong, Wenjing Wang, Shilei Liu, Central South University, China; Yinan Li, Hao Li, the China Academy of Space Technology (Xi’an), China
TH-A3.1P.4: The Use of In-situ Instruments for Snowflake and Snowfall Analysis to Constrain Scattering Winter Observations by Weather Radars
Hein Thant, Branislav Notaroš, Colorado State University, United States
TH-A3.1P.5: Ground Moving Target Detection Using Geometric Feature Based Machine Learning Classifier
Rafi Ahmed, Florida International University, United States; Hai Deng, Nanjing University of Aeronautics and Astronautics, China
Resources
No resources available.