198 citations · 458 across the 34 of their papers we have counts for
5 papers · 1 filter
Inverse deep learning methods and benchmarks for artificial electromagnetic material design
Simiao Ren, Ashwin Mahendra, Omar Khatib +3
Deep learning (DL) inverse techniques have increased the speed of artificial electromagnetic material (AEM) design and improved the quality of resulting devices. Many DL inverse te…
Blaschke Product Neural Networks (BPNN): A Physics-Infused Neural Network for Phase Retrieval of Meromorphic Functions
Juncheng Dong, Simiao Ren, Yang Deng +5
Numerous physical systems are described by ordinary or partial differential equations whose solutions are given by holomorphic or meromorphic functions in the complex domain. In ma…
SIMPL: Generating Synthetic Overhead Imagery to Address Zero-shot and Few-Shot Detection Problems
Yang Xu, Bohao Huang, Xiong Luo +2
Recently deep neural networks (DNNs) have achieved tremendous success for object detection in overhead (e.g., satellite) imagery. One ongoing challenge however is the acquisition o…
Randomized Histogram Matching: A Simple Augmentation for Unsupervised Domain Adaptation in Overhead Imagery
Can Yaras, Kaleb Kassaw, Bohao Huang +2
Modern deep neural networks (DNNs) are highly accurate on many recognition tasks for overhead (e.g., satellite) imagery. However, visual domain shifts (e.g., statistical changes du…
GridTracer: Automatic Mapping of Power Grids using Deep Learning and Overhead Imagery
Bohao Huang, Jichen Yang, Artem Streltsov +3
Energy system information valuable for electricity access planning such as the locations and connectivity of electricity transmission and distribution towers, termed the power grid…