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Jordan M. Malof
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Books and Theses
- 2015
- [b1]Jordan M. Malof:
Statistical Models for Improving the Rate of Advance of Buried Target Detection Systems. Duke University, Durham, NC, USA, 2015
Journal Articles
- 2024
- [j10]Can Yaras
, Kaleb Kassaw
Randomized Histogram Matching: A Simple Augmentation for Unsupervised Domain Adaptation in Overhead Imagery. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 17: 1988-1998 (2024) - 2022
- [j9]Simiao Ren
Utilizing Geospatial Data for Assessing Energy Security: Mapping Small Solar Home Systems Using Unmanned Aerial Vehicles and Deep Learning. ISPRS Int. J. Geo Inf. 11(4): 222 (2022) - [j8]Zachary D. Calhoun
Self-Supervised Encoders Are Better Transfer Learners in Remote Sensing Applications. Remote. Sens. 14(21): 5500 (2022) - [j7]Yang Xu
SIMPL: Generating Synthetic Overhead Imagery to Address Custom Zero-Shot and Few-Shot Detection Problems. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 15: 4386-4396 (2022) - [j6]Bohao Huang
GridTracer: Automatic Mapping of Power Grids Using Deep Learning and Overhead Imagery. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 15: 4956-4970 (2022) - 2019
- [j5]Jordan M. Malof
A Large-Scale Multi-Institutional Evaluation of Advanced Discrimination Algorithms for Buried Threat Detection in Ground Penetrating Radar. IEEE Trans. Geosci. Remote. Sens. 57(9): 6929-6945 (2019) - 2018
- [j4]Daniël Reichman
On Choosing Training and Testing Data for Supervised Algorithms in Ground-Penetrating Radar Data for Buried Threat Detection. IEEE Trans. Geosci. Remote. Sens. 56(1): 497-507 (2018) - [j3]Joseph A. Camilo
A Large Comparison of Feature-Based Approaches for Buried Target Classification in Forward-Looking Ground-Penetrating Radar. IEEE Trans. Geosci. Remote. Sens. 56(1): 547-558 (2018) - 2016
- [j2]Jordan M. Malof
A Probabilistic Model for Designing Multimodality Landmine Detection Systems to Improve Rates of Advance. IEEE Trans. Geosci. Remote. Sens. 54(9): 5258-5270 (2016) - 2012
- [j1]Jordan M. Malof, Maciej A. Mazurowski, Georgia D. Tourassi
The effect of class imbalance on case selection for case-based classifiers: An empirical study in the context of medical decision support. Neural Networks 25: 141-145 (2012)
Conference and Workshop Papers
- 2024
- [c30]Marlyne Hakizimana, Emelia Mavis, Yuting Chiu, Jordan M. Malof, Kyle Bradbury:
Enhanced Remote Sensing Model Performance Through Self-Supervised Learning with Multi-Spectral Data. IGARSS 2024: 2833-2836 - [c29]Simiao Ren, Francesco Luzi, Saad Lahrichi, Kaleb Kassaw, Leslie M. Collins, Kyle Bradbury, Jordan M. Malof:
Segment anything, from space? WACV 2024: 8340-8350 - 2023
- [c28]Gregory P. Spell, Simiao Ren, Leslie M. Collins, Jordan M. Malof:
Mixture Manifold Networks: A Computationally Efficient Baseline for Inverse Modeling. AAAI 2023: 9874-9881 - [c27]Francesco Luzi, Aneesh Gupta, Leslie M. Collins, Kyle Bradbury
Transformers For Recognition In Overhead Imagery: A Reality Check. WACV 2023: 3767-3776 - 2022
- [c26]Juncheng Dong, Simiao Ren, Yang Deng, Omar Khatib, Jordan M. Malof, Mohammadreza Soltani, Willie Padilla, Vahid Tarokh:
Blaschke Product Neural Networks (BPNN): A Physics-Infused Neural Network for Phase Retrieval of Meromorphic Functions. ICLR 2022 - 2021
- [c25]Gregory P. Spell, Leslie M. Collins, Jordan M. Malof:
Application of Compositional Neural Networks for Robust Classification of Infrared Imagery. IGARSS 2021: 2799-2802 - [c24]Wei Hu
Wind Turbine Detection with Synthetic Overhead Imagery. IGARSS 2021: 4908-4911 - [c23]Yang Deng, Juncheng Dong, Simiao Ren, Omar Khatib, Mohammadreza Soltani, Vahid Tarokh, Willie Padilla, Jordan M. Malof:
Benchmarking Data-driven Surrogate Simulators for Artificial Electromagnetic Materials. NeurIPS Datasets and Benchmarks 2021 - 2020
- [c22]Varun Nair, Paul Rhee, Jichen Yang
Designing Synthetic Overhead Imagery to Match a Target Geographic Region: Preliminary Results Training Deep Learning Models. IGARSS 2020: 948-951 - [c21]Bohao Huang, Kyle Bradbury
Do Deep Learning Models Generalize to Overhead Imagery from Novel Geographic Domains? The xGD Benchmark Problem. IGARSS 2020: 1476-1479 - [c20]Wei Hu
Mapping Electric Transmission Line Infrastructure from Aerial Imagery with Deep Learning. IGARSS 2020: 2229-2232 - [c19]Simiao Ren, Willie Padilla, Jordan M. Malof:
Benchmarking Deep Inverse Models over time, and the Neural-Adjoint method. NeurIPS 2020 - [c18]Fanjie Kong, Bohao Huang, Kyle Bradbury
The Synthinel-1 dataset: a collection of high resolution synthetic overhead imagery for building segmentation. WACV 2020: 1803-1812 - 2019
- [c17]Kangcheng Lin, Bohao Huang, Leslie M. Collins, Kyle Bradbury
A simple rotational equivariance loss for generic convolutional segmentation networks: preliminary results. IGARSS 2019: 3876-3879 - [c16]Fanjie Kong, Cheng Chen, Bohao Huang, Leslie M. Collins, Kyle Bradbury
Training a single multi-class convolutional segmentation network using multiple datasets with heterogeneous labels: preliminary results. IGARSS 2019: 3903-3906 - 2018
- [c15]Artem Streltsov, Kyle Bradbury
Automated Building Energy Consumption Estimation from Aerial Imagery. IGARSS 2018: 1676-1679 - [c14]Rui Wang, Leslie M. Collins, Kyle Bradbury
Semisupervised Adversarial Discriminative Domain Adaptation, with Applicationto Remote Sensing Data. IGARSS 2018: 3611-3614 - [c13]Bohao Huang, Daniel Reichman, Leslie M. Collins, Kyle Bradbury
On The Extraction of Training Imagery from Very Large Remote Sensing Datasets for Deep Convolutional Segmenatation Networks. IGARSS 2018: 6895-6898 - [c12]Bohao Huang, Leslie M. Collins, Kyle Bradbury
Deep Convolutional Segmentation of Remote Sensing Imagery: A Simple and Efficient Alternative to Stitching Output Labels. IGARSS 2018: 6899-6902 - [c11]Bohao Huang, Kangkang Lu, Nicolas Audebert
Large-Scale Semantic Classification: Outcome of the First Year of Inria Aerial Image Labeling Benchmark. IGARSS 2018: 6947-6950 - 2017
- [c10]Jordan M. Malof, Sravya Chelikani, Leslie M. Collins, Kyle Bradbury
Trading spatial resolution for improved accuracy in remote sensing imagery: an empirical study using synthetic data. AIPR 2017: 1-7 - [c9]Rui Wang, Joseph A. Camilo, Leslie M. Collins, Kyle Bradbury
The poor generalization of deep convolutional networks to aerial imagery from new geographic locations: an empirical study with solar array detection. AIPR 2017: 1-8 - [c8]Rui Wang, Joseph A. Camilo, Leslie M. Collins, Kyle Bradbury
The poor generalization of deep convolutional networks to aerial imagery from new geographic locations: an empirical study with solar array detection. AIPR 2017: 1-8 - [c7]Jordan M. Malof, Leslie M. Collins, Kyle Bradbury
A deep convolutional neural network, with pre-training, for solar photovoltaic array detection in aerial imagery. IGARSS 2017: 874-877 - [c6]Brenda So, Cory Nezin, Vishnu Kaimal, Sam Keene, Leslie M. Collins, Kyle Bradbury
Estimating the electricity generation capacity of solar photovoltaic arrays using only color aerial imagery. IGARSS 2017: 1603-1606 - [c5]Shengxin Qian, Sravya Chelikani, Patrick Wang, Leslie M. Collins, Kyle Bradbury
Trading spatial resolution for improved accuracy when using detection algorithms on remote sensing imagery. IGARSS 2017: 3716-3719 - 2016
- [c4]Daniël Reichman, Jordan M. Malof, Leslie M. Collins:
Leveraging seed dictionaries to improve dictionary learning. ICIP 2016: 3723-3727 - 2011
- [c3]Jordan M. Malof, Adam E. Gaweda:
Optimizing drug therapy with Reinforcement Learning: The case of Anemia Management. IJCNN 2011: 2088-2092 - 2009
- [c2]Jordan M. Malof, Maciej A. Mazurowski, Georgia D. Tourassi
The effect of class imbalance on case selection for case-based classifiers, with emphasis on computer-aided diagnosis systems. IJCNN 2009: 1975-1980 - [c1]Maciej A. Mazurowski, Jordan M. Malof, Jacek M. Zurada, Georgia D. Tourassi
A comparative study of database reduction methods for case-based computer-aided detection systems: preliminary results. Computer-Aided Diagnosis 2009: 72600F
Informal and Other Publications
- 2024
- [i26]Darui Lu, Yang Deng, Jordan M. Malof, Willie J. Padilla:
Can Large Language Models Learn the Physics of Metamaterials? An Empirical Study with ChatGPT. CoRR abs/2404.15458 (2024) - [i25]Kaleb Kassaw, Francesco Luzi, Leslie M. Collins, Jordan M. Malof:
Are Deep Learning Models Robust to Partial Object Occlusion in Visual Recognition Tasks? CoRR abs/2409.10775 (2024) - 2023
- [i24]Simiao Ren, Yang Deng, Willie J. Padilla, Leslie M. Collins, Jordan M. Malof:
Deep Active Learning for Scientific Computing in the Wild. CoRR abs/2302.00098 (2023) - [i23]Simiao Ren, Francesco Luzi, Saad Lahrichi, Kaleb Kassaw, Leslie M. Collins, Kyle Bradbury
Segment anything, from space? CoRR abs/2304.13000 (2023) - [i22]Rixi Peng, Juncheng Dong, Jordan M. Malof, Willie J. Padilla, Vahid Tarokh:
Deep Generalized Green's Functions. CoRR abs/2306.02925 (2023) - 2022
- [i21]Simiao Ren, Yang Deng, Willie J. Padilla, Jordan M. Malof:
Hyperparameter-free deep active learning for regression problems via query synthesis. CoRR abs/2201.12632 (2022) - [i20]Simiao Ren, Wei Hu, Kyle Bradbury, Dylan Harrison-Atlas, Laura Malaguzzi Valeri, Brian Murray, Jordan M. Malof:
Automated Extraction of Energy Systems Information from Remotely Sensed Data: A Review and Analysis. CoRR abs/2202.12939 (2022) - [i19]Handi Yu, Leslie M. Collins, Jordan M. Malof:
Meta-simulation for the Automated Design of Synthetic Overhead Imagery. CoRR abs/2209.08685 (2022) - [i18]Francesco Luzi, Aneesh Gupta, Leslie M. Collins, Kyle Bradbury
Transformers For Recognition In Overhead Imagery: A Reality Check. CoRR abs/2210.12599 (2022) - [i17]Gregory P. Spell, Simiao Ren, Leslie M. Collins, Jordan M. Malof:
Mixture Manifold Networks: A Computationally Efficient Baseline for Inverse Modeling. CoRR abs/2211.14366 (2022) - [i16]Evelyn A. Stump, Francesco Luzi, Leslie M. Collins, Jordan M. Malof:
Meta-Learning for Color-to-Infrared Cross-Modal Style Transfer. CoRR abs/2212.12824 (2022) - 2021
- [i15]Bohao Huang, Jichen Yang, Artem Streltsov, Kyle Bradbury, Leslie M. Collins, Jordan M. Malof:
GridTracer: Automatic Mapping of Power Grids using Deep Learning and Overhead Imagery. CoRR abs/2101.06390 (2021) - [i14]Can Yaris, Bohao Huang, Kyle Bradbury, Jordan M. Malof:
Randomized Histogram Matching: A Simple Augmentation for Unsupervised Domain Adaptation in Overhead Imagery. CoRR abs/2104.14032 (2021) - [i13]Yang Xu, Bohao Huang, Xiong Luo, Kyle Bradbury, Jordan M. Malof:
SIMPL: Generating Synthetic Overhead Imagery to Address Zero-shot and Few-Shot Detection Problems. CoRR abs/2106.15681 (2021) - [i12]Juncheng Dong, Simiao Ren, Yang Deng, Omar Khatib, Jordan M. Malof, Mohammadreza Soltani, Willie Padilla, Vahid Tarokh:
Blaschke Product Neural Networks (BPNN): A Physics-Infused Neural Network for Phase Retrieval of Meromorphic Functions. CoRR abs/2111.13311 (2021) - [i11]Simiao Ren, Ashwin Mahendra, Omar Khatib, Yang Deng, Willie J. Padilla, Jordan M. Malof:
Inverse deep learning methods and benchmarks for artificial electromagnetic material design. CoRR abs/2112.10254 (2021) - 2020
- [i10]Fanjie Kong, Bohao Huang, Kyle Bradbury, Jordan M. Malof:
The Synthinel-1 dataset: a collection of high resolution synthetic overhead imagery for building segmentation. CoRR abs/2001.05130 (2020) - [i9]Simiao Ren, Willie Padilla, Jordan M. Malof:
Benchmarking deep inverse models over time, and the neural-adjoint method. CoRR abs/2009.12919 (2020) - 2019
- [i8]Jordan M. Malof, Boning Li, Bohao Huang, Kyle Bradbury, Artem Stretslov:
Mapping solar array location, size, and capacity using deep learning and overhead imagery. CoRR abs/1902.10895 (2019) - 2018
- [i7]Joseph A. Camilo, Rui Wang, Leslie M. Collins, Kyle Bradbury, Jordan M. Malof:
Application of a semantic segmentation convolutional neural network for accurate automatic detection and mapping of solar photovoltaic arrays in aerial imagery. CoRR abs/1801.04018 (2018) - [i6]Jordan M. Malof, Daniël Reichman, Andrew Karem, Hichem Frigui, Dominic K. C. Ho, Joseph N. Wilson, Wen-Hsiung Lee, William Cummings, Leslie M. Collins:
A Large-Scale Multi-Institutional Evaluation of Advanced Discrimination Algorithms for Buried Threat Detection in Ground Penetrating Radar. CoRR abs/1803.03729 (2018) - [i5]Bohao Huang, Daniel Reichman, Leslie M. Collins, Kyle Bradbury, Jordan M. Malof:
Dense labeling of large remote sensing imagery with convolutional neural networks: a simple and faster alternative to stitching output label maps. CoRR abs/1805.12219 (2018) - [i4]Daniel Reichman, Leslie M. Collins, Jordan M. Malof:
gprHOG: Several Simple Improvements to the Histogram of Oriented Gradients Feature for Threat Detection in Ground-Penetrating Radar. CoRR abs/1806.01349 (2018) - 2017
- [i3]Joseph A. Camilo, Leslie M. Collins, Jordan M. Malof:
A large comparison of feature-based approaches for buried target classification in forward-looking ground-penetrating radar. CoRR abs/1702.03000 (2017) - 2016
- [i2]Jordan M. Malof, Kyle Bradbury, Leslie M. Collins, Richard G. Newell:
Automatic Detection of Solar Photovoltaic Arrays in High Resolution Aerial Imagery. CoRR abs/1607.06029 (2016) - [i1]Daniël Reichman, Leslie M. Collins, Jordan M. Malof:
On Choosing Training and Testing Data for Supervised Algorithms in Ground Penetrating Radar Data for Buried Threat Detection. CoRR abs/1612.03477 (2016)
Coauthor Index
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