WE-SP.3A.1: Multiphysics Joint Inversion Using Successive Deep Perceptual Constraints
Yanyan Hu, Jiefu Chen, Xuqing Wu, University of Houston, United States; Yueqin Huang, Cyentech, United States
WE-SP.3A.2: AI-Enhanced Global Optimization for Microwave Brain Imaging
Francesco Zardi, Marco Salucci, Lorenzo Poli, Andrea Massa, ELEDIA@UniTN - University of Trento, Italy
WE-SP.3A.3: Efficient Data Generation for Stroke Classification via Multilayer Perceptron
Valeria Mariano, Jorge Alberto Tobon Vasquez, Mario R. Casu, Francesca Vipiana, Politecnico di Torino, Italy
WE-SP.3A.4: Microwave Data Inversion With a Model Compression Scheme Based on Deep Learning
Rui Guo, Zhichao Lin, Maokun Li, Fan Yang, Shenheng Xu, Tsinghua University, China; Aria Abubakar, Schlumberger, China
WE-SP.3A.5: Combined Machine Learning- Inversion Scheme for Super-Resolution 3-Dimensional Microwave Human Brain Imaging
Le-Yi Zhao, Li-Ye Xiao, Yu Cheng, Xiamen University, China; QingHuo Liu, Duke University, China
WE-SP.3A.6: 3D-printed gear system for antenna motion in an MR environment: initial phantom imaging experiments
Paul Meaney, Timothy Raynolds, Shireen Geimer, Grace Player, Keith Paulsen, Dartmouth College, United States; Xiaoyu Yang, Quality Electrodynamics, United States
WE-SP.3A.7: A hybrid CNN-NGBoost model for probabilistic image-driven path loss prediction
Sotirios Sotiroudis, Sotirios Goudos, Aristotle University of Thessaloniki, Greece; Christos Christodoulou, University of New Mexico, United States
WE-SP.3A.8: Semantic Segmentation of Xenograft Tumor Tissues Imaged with Pulsed Terahertz Technology
Haoyan Liu, Nagma Vohra, Magda El-Shenawee, Alexander Nelson, University of Arkansas, Fayetteville, United States; Keith Bailey, Charles River Laboratories, United States
WE-SP.3A.9: On the Use of Machine Learning and Deep Learning for Radar- Based Passenger Monitoring
Hajar Abedi, Martin Ma, Jennifer Yu, James He, Ahmad Ansariyan, George Shaker, University of Waterloo, Canada
