FR-A3.1A.4
CNN-Based Hotspot Detection in Small-Scale Composting from Multistatic Microwave Time-Domain Responses
Alex Ramiro Masaquiza-Caiza, politecnico di torino, Italy; Alejandro Rangel-Retavisca, Universidad Nacional de Colombia, Colombia; David Orlando Rodriguez-Duarte, politecnico di torino, Italy
Session:
AI Methods in Propagation and Imaging Oral
Track:
AP-S: Track 3: Propagation and Scattering
Location:
Room 353
Session Time:
Fri, 17 Jul, 08:00 - 09:40
Presentation Time:
Fri, 17 Jul, 09:00 - 09:20
Presentation
Discussion
Session FR-A3.1A
FR-A3.1A.1: A Physics-Informed Diffusion Model for Generating Focusing Electromagnetic Wave Morphology in Disordered Scattering Scenarios
Jinyan Ma, Da Li, Jiahui Wang, Ruifeng Li, Chongwen Huang, Erping Li, Zhejiang University, China
FR-A3.1A.2: Numerical Study of an AI-Augmented MIMO GPR System for Non-Destructive Measurement of Underground Potato Tuber Characteristics
Taorui Chen, Yi Wang, Hai-Han Sun, University of Wisconsin - Madison, United States
FR-A3.1A.3: Adjustment of Cluster-Then-Predict Framework for Multiport Scatterer Load Prediction
Hanjun Park, Pohang University of Science and Technology (POSTECH), Korea (South); Aleksandr Kuznetsov, Ville Viikari, Aalto University, Finland
FR-A3.1A.4: CNN-Based Hotspot Detection in Small-Scale Composting from Multistatic Microwave Time-Domain Responses
Alex Ramiro Masaquiza-Caiza, politecnico di torino, Italy; Alejandro Rangel-Retavisca, Universidad Nacional de Colombia, Colombia; David Orlando Rodriguez-Duarte, politecnico di torino, Italy
FR-A3.1A.5: Deep Learning Surrogate Modeling of Body-Area Networks via Equivalent Electromagnetic Sources
Shalitha Pathiranage, Xiaoyuan Sun, Yang Hao, Queen Mary University of London, United Kingdom; Jiang Zhu, Javier De Luis, Peter Renner, Djordje Tujkovic, Meta Platforms, Inc., United States
Resources
No resources available.