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20172022
most citedApplication of a semantic segmentation convolutional neural network for accurate automatic detection and mapping of solar photovoltaic arrays in aerial imagery

29 citations · 35 across the 10 of their papers we have counts for

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Showing cs.CVShow all

8 papers · 1 filter

cs.CV2022

Transformers For Recognition In Overhead Imagery: A Reality Check

Francesco Luzi, Aneesh Gupta, Leslie Collins +2

There is evidence that transformers offer state-of-the-art recognition performance on tasks involving overhead imagery (e.g., satellite imagery). However, it is difficult to make u…

cs.CV2022

Meta-simulation for the Automated Design of Synthetic Overhead Imagery

Handi Yu, Simiao Ren, Leslie M. Collins +1

The use of synthetic (or simulated) data for training machine learning models has grown rapidly in recent years. Synthetic data can often be generated much faster and more cheaply…

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…

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…

cs.CV2018

A Large-Scale Multi-Institutional Evaluation of Advanced Discrimination Algorithms for Buried Threat Detection in Ground Penetrating Radar

Jordan M. Malof, Daniel Reichman, Andrew Karem +6

In this paper we consider the development of algorithms for the automatic detection of buried threats using ground penetrating radar (GPR) measurements. GPR is one of the most stud…