IEEE AP-S/URSI 2023 || Portland, Oregon, USA || 23-28 July 2023

Institute of Electrical and Electronics Engineers (IEEE)

International Union of Radio Science

IEEE APS

U.S. NATIONAL COMMITTEE FOR URSI

National Academies Sciences Engineering Medicine

IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting

July 23–28, 2023 • Portland, Oregon, USA

23-28 July 2023 • Portland, Oregon, USA

IEEE AP-S/URSI 2023

23-28 July 2023 • Portland, Oregon, USA

FR-A4.1P.3

Embedding General Antenna Patterns in Machine Learning Based Propagation Models

Aristeidis Seretis, Costas Sarris, University of Toronto, Canada

Session:

EM Modeling and Machine learning for Scattering and Propagation

Track:

AP-S: Propagation & Scattering

Location:

C 120-122 (OCC)

Session Time:

Fri, 28 Jul, 15:20 - 17:00 PDT (UTC -7)

Presentation Time:

Fri, 28 Jul, 16:00 - 16:20 PDT (UTC -7)

Session Co-Chairs:

Francesco Andriulli, Politecnico di Torino and Shutong Qi, University of Toronto

Session FR-A4.1P

FR-A4.1P.1: Learning From Noise: An Unsupervised GPR Data Denoising Scheme based on Generative Adversarial Networks

Qiqi Dai, Yee Hui Lee, Nanyang Technological University, Singapore, Singapore; Mohamed Lokman Mohd Yusof, Daryl Lee, National Parks Board, Singapore; Abdulkadir C. Yucel, Nanyang Technological University, Singapore

FR-A4.1P.2: Bistatic Scattering Analysis of Vegetation using Fast Hybrid Method of Full Wave Simulations

Jongwoo Jeong, Leung Tsang, University of Michigan, United States; Andreas Colliander, Simon Yueh, California Institute of Technology, United States

FR-A4.1P.3: Embedding General Antenna Patterns in Machine Learning Based Propagation Models

Aristeidis Seretis, Costas Sarris, University of Toronto, Canada