フォロー
Jordan M Malof
Jordan M Malof
Assistant Professor, University of Montana
確認したメール アドレス: duke.edu - ホームページ
タイトル
引用先
引用先
Deep learning for accelerated all-dielectric metasurface design
CC Nadell, B Huang, JM Malof, WJ Padilla
Optics express 27 (20), 27523-27535, 2019
3492019
Automatic detection of solar photovoltaic arrays in high resolution aerial imagery
JM Malof, K Bradbury, LM Collins, RG Newell
Applied energy 183, 229-240, 2016
1602016
Imaging descriptors improve the predictive power of survival models for glioblastoma patients
MA Mazurowski, A Desjardins, JM Malof
Neuro-Oncology, 2013
1192013
Distributed solar photovoltaic array location and extent dataset for remote sensing object identification
K Bradbury, R Saboo, T L Johnson, JM Malof, A Devarajan, W Zhang, ...
Scientific data 3 (1), 1-9, 2016
1002016
Large-scale semantic classification: outcome of the first year of inria aerial image labeling benchmark
B Huang, K Lu, N Audeberr, A Khalel, Y Tarabalka, J Malof, A Boulch, ...
IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium …, 2018
992018
Deep learning the electromagnetic properties of metamaterials—a comprehensive review
O Khatib, S Ren, J Malof, WJ Padilla
Advanced Functional Materials 31 (31), 2101748, 2021
972021
Automatic solar photovoltaic panel detection in satellite imagery
JM Malof, R Hou, LM Collins, K Bradbury, R Newell
2015 International Conference on Renewable Energy Research and Applications …, 2015
922015
Some good practices for applying convolutional neural networks to buried threat detection in Ground Penetrating Radar
D Reichman, LM Collins, JM Malof
2017 9th International Workshop on Advanced Ground Penetrating Radar (IWAGPR …, 2017
732017
A deep convolutional neural network, with pre-training, for solar photovoltaic array detection in aerial imagery
JM Malof, LM Collins, K Bradbury
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2017
672017
Neural-adjoint method for the inverse design of all-dielectric metasurfaces
Y Deng, S Ren, K Fan, JM Malof, WJ Padilla
Optics Express 29 (5), 7526-7534, 2021
642021
A deep convolutional neural network and a random forest classifier for solar photovoltaic array detection in aerial imagery
JM Malof, LM Collins, K Bradbury, RG Newell
2016 IEEE International conference on renewable energy research and …, 2016
612016
Improving convolutional neural networks for buried target detection in ground penetrating radar using transfer learning via pretraining
J Bralich, D Reichman, LM Collins, JM Malof
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXII …, 2017
592017
Estimating residential building energy consumption using overhead imagery
A Streltsov, JM Malof, B Huang, K Bradbury
Applied Energy 280, 116018, 2020
522020
Application of a semantic segmentation convolutional neural network for accurate automatic detection and mapping of solar photovoltaic arrays in aerial imagery
J Camilo, R Wang, LM Collins, K Bradbury, JM Malof
arXiv preprint arXiv:1801.04018, 2018
512018
The Synthinel-1 dataset: a collection of high resolution synthetic overhead imagery for building segmentation
F Kong, B Huang, K Bradbury, JM Malof
(WACV 2020) IEEE Winter Conference on Applications of Computer Vision (WACV), 2020
462020
Benchmarking Deep Inverse Models over time, and the Neural-Adjoint method
S Ren, WJ Padilla, JM Malof
(NeurIPS 2020) Advances in Neural Information Processing Systems 33, 38--48, 2020
462020
The effect of class imbalance on case selection for case-based classifiers: An empirical study in the context of medical decision support
JM Malof, MA Mazurowski, GD Tourassi
Neural Networks 25, 141-145, 2012
442012
A large-scale multi-institutional evaluation of advanced discrimination algorithms for buried threat detection in ground penetrating radar
JM Malof, D Reichman, A Karem, H Frigui, KC Ho, JN Wilson, WH Lee, ...
IEEE Transactions on Geoscience and Remote Sensing 57 (9), 6929-6945, 2019
432019
Tiling and stitching segmentation output for remote sensing: Basic challenges and recommendations
B Huang, D Reichman, LM Collins, K Bradbury, JM Malof
arXiv preprint arXiv:1805.12219, 2018
392018
On choosing training and testing data for supervised algorithms in ground-penetrating radar data for buried threat detection
D Reichman, LM Collins, JM Malof
IEEE Transactions on Geoscience and Remote Sensing 56 (1), 497-507, 2017
332017
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