activity
20182022
most citedApplication of a semantic segmentation convolutional neural network for accurate automatic detection and mapping of solar photovoltaic arrays in aerial imagery

29 citations · 34 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CV2021

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…

cs.CV20212 cited

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…

physics.optics20203 cited

Neural-adjoint method for the inverse design of all-dielectric metasurfaces

Yang Deng, Simiao Ren, Kebin Fan +2

All-dielectric metasurfaces exhibit exotic electromagnetic responses, similar to those obtained with metal-based metamaterials. Research in all-dielectric metasurfaces currently us…

cs.CV2020

The Synthinel-1 dataset: a collection of high resolution synthetic overhead imagery for building segmentation

Fanjie Kong, Bohao Huang, Kyle Bradbury +1

Recently deep learning - namely convolutional neural networks (CNNs) - have yielded impressive performance for the task of building segmentation on large overhead (e.g., satellite)…

cs.CV2018

gprHOG and the popularity of Histogram of Oriented Gradients (HOG) for Buried Threat Detection in Ground-Penetrating Radar

Daniel Reichman, Leslie M. Collins, Jordan M. Malof

Substantial research has been devoted to the development of algorithms that automate buried threat detection (BTD) with ground penetrating radar (GPR) data, resulting in a large nu…

cs.CV2018

Tiling and Stitching Segmentation Output for Remote Sensing: Basic Challenges and Recommendations

Bohao Huang, Daniel Reichman, Leslie M. Collins +2

In this work we consider the application of convolutional neural networks (CNNs) for pixel-wise labeling (a.k.a., semantic segmentation) of remote sensing imagery (e.g., aerial col…