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04/25/2023
Segment anything, from space?
Recently, the first foundation model developed specifically for vision t...
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12/24/2022
Meta-Learning for Color-to-Infrared Cross-Modal Style Transfer
Recent object detection models for infrared (IR) imagery are based upon ...
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11/25/2022
Mixture Manifold Networks: A Computationally Efficient Baseline for Inverse Modeling
We propose and show the efficacy of a new method to address generic inve...
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09/19/2022
Meta-simulation for the Automated Design of Synthetic Overhead Imagery
The use of synthetic (or simulated) data for training machine learning m...
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12/19/2021
Inverse deep learning methods and benchmarks for artificial electromagnetic material design
Deep learning (DL) inverse techniques have increased the speed of artifi...
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06/29/2021
SIMPL: Generating Synthetic Overhead Imagery to Address Zero-shot and Few-Shot Detection Problems
Recently deep neural networks (DNNs) have achieved tremendous success fo...
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04/28/2021
Randomized Histogram Matching: A Simple Augmentation for Unsupervised Domain Adaptation in Overhead Imagery
Modern deep neural networks (DNNs) achieve highly accurate results for m...
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01/15/2020
The Synthinel-1 dataset: a collection of high resolution synthetic overhead imagery for building segmentation
Recently deep learning - namely convolutional neural networks (CNNs) - h...
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02/28/2019
Mapping solar array location, size, and capacity using deep learning and overhead imagery
The effective integration of distributed solar photovoltaic (PV) arrays ...
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06/04/2018
gprHOG: Several Simple Improvements to the Histogram of Oriented Gradients Feature for Threat Detection in Ground-Penetrating Radar
The ground penetrating radar (GPR) is one of the most successful remote ...
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05/30/2018
Dense labeling of large remote sensing imagery with convolutional neural networks: a simple and faster alternative to stitching output label maps
In this work we consider the application of convolutional neural network...
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03/10/2018
A Large-Scale Multi-Institutional Evaluation of Advanced Discrimination Algorithms for Buried Threat Detection in Ground Penetrating Radar
In this paper we consider the development of algorithms for the automati...
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01/11/2018
Application of a semantic segmentation convolutional neural network for accurate automatic detection and mapping of solar photovoltaic arrays in aerial imagery
We consider the problem of automatically detecting small-scale solar pho...
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02/09/2017
A large comparison of feature-based approaches for buried target classification in forward-looking ground-penetrating radar
Forward-looking ground-penetrating radar (FLGPR) has recently been inves...
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12/11/2016