no code implementations • 25 Apr 2023 • Simiao Ren, Francesco Luzi, Saad Lahrichi, Kaleb Kassaw, Leslie M. Collins, Kyle Bradbury, Jordan M. Malof
In this work, we examine whether SAM's performance extends to overhead imagery problems and help guide the community's response to its development.
no code implementations • 24 Dec 2022 • Evelyn A. Stump, Francesco Luzi, Leslie M. Collins, Jordan M. Malof
To address this problem, we explore cross-modal style transfer (CMST) to leverage large and diverse color imagery datasets so that they can be used to train DNN-based IR image based object detectors.
no code implementations • 25 Nov 2022 • Gregory P. Spell, Simiao Ren, Leslie M. Collins, Jordan M. Malof
We propose and show the efficacy of a new method to address generic inverse problems.
no code implementations • 19 Sep 2022 • Handi Yu, Simiao Ren, Leslie M. Collins, Jordan M. Malof
The use of synthetic (or simulated) data for training machine learning models has grown rapidly in recent years.
no code implementations • 28 May 2021 • Kevin M. Chu, Leslie M. Collins, Boyla O. Mainsah
This study proposes a phoneme-based mask estimation algorithm, where separate mask estimation models are trained for each phoneme.
no code implementations • 28 May 2021 • Kevin M. Chu, Leslie M. Collins, Boyla O. Mainsah
Over the past year, remote speech intelligibility testing has become a popular and necessary alternative to traditional in-person experiments due to the need for physical distancing during the COVID-19 pandemic.
no code implementations • 6 May 2021 • Anish Karpurapu, Adam Krekorian, Ye Tian, Leslie M. Collins, Ravi Karra, Aaron Franklin, Boyla O. Mainsah
Since a sequence of prior doses and INR better capture the variability in individual warfarin response, we hypothesized that longitudinal dose response data will improve maintenance dose predictions.
no code implementations • 16 Jan 2021 • Bohao Huang, Jichen Yang, Artem Streltsov, Kyle Bradbury, Leslie M. Collins, Jordan Malof
Energy system information valuable for electricity access planning such as the locations and connectivity of electricity transmission and distribution towers, termed the power grid, is often incomplete, outdated, or altogether unavailable.
no code implementations • 4 Jun 2018 • 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 number of proposed algorithms.
no code implementations • 30 May 2018 • Bohao Huang, Daniel Reichman, Leslie M. Collins, Kyle Bradbury, Jordan M. Malof
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 color or hyperspectral imagery).
Segmentation Of Remote Sensing Imagery Semantic Segmentation
no code implementations • 10 Mar 2018 • Jordan M. Malof, Daniel Reichman, Andrew Karem, Hichem Frigui, Dominic K. C. Ho, Joseph N. Wilson, Wen-Hsiung Lee, William Cummings, Leslie M. Collins
In this work we report the results of a multi-institutional effort to develop advanced buried threat detection algorithms for a real-world GPR BTD system.
no code implementations • 11 Jan 2018 • Joseph Camilo, Rui Wang, Leslie M. Collins, Kyle Bradbury, Jordan M. Malof
In this work, we employ a state-of-the-art convolutional neural network architecture, called SegNet (Badrinarayanan et.
no code implementations • 9 Feb 2017 • Joseph A. Camilo, Leslie M. Collins, Jordan M. Malof
The first goal of this work is to provide a comprehensive comparison of detection performance using existing features on a large collection of FLGPR data.
no code implementations • 11 Dec 2016 • Daniël Reichman, Leslie M. Collins, Jordan M. Malof
Training data most often consists of 2-dimensional images (or patches) of GPR data, from which features are extracted, and provided to the classifier during training and testing.
no code implementations • 20 Jul 2016 • Jordan M. Malof, Kyle Bradbury, Leslie M. Collins, Richard G. Newell
Unfortunately, existing methods for obtaining this information, such as surveys and utility interconnection filings, are limited in their completeness and spatial resolution.