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Nathan Inkawhich
Nathan Inkawhich
Researcher at Air Force Research Laboratory
Correu electrònic verificat a us.af.mil
Títol
Citada per
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Feature space perturbations yield more transferable adversarial examples
N Inkawhich, W Wen, HH Li, Y Chen
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
2352019
DVERGE: diversifying vulnerabilities for enhanced robust generation of ensembles
H Yang, J Zhang, H Dong, N Inkawhich, A Gardner, A Touchet, W Wilkes, ...
Advances in Neural Information Processing Systems (NeurIPS), 2020
1332020
Transferable Perturbations of Deep Feature Distributions
N Inkawhich, KJ Liang, L Carin, Y Chen
International Conference on Learning Representations (ICLR), 2020
1002020
Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability
N Inkawhich, KJ Liang, B Wang, M Inkawhich, L Carin, Y Chen
Advances in Neural Information Processing Systems (NeurIPS), 2020
912020
Bridging a Gap in SAR-ATR: Training on Fully Synthetic and Testing on Measured Data
N Inkawhich, MJ Inkawhich, E Davis, U Majumder, E Tripp, CT Capraro, ...
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
902021
Mixture outlier exposure: Towards out-of-distribution detection in fine-grained environments
J Zhang, N Inkawhich, R Linderman, Y Chen, H Li
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023
532023
NTIRE 2021 multi-modal aerial view object classification challenge
J Liu, N Inkawhich, O Nina, R Timofte
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
462021
Adversarial attacks for optical flow-based action recognition classifiers
N Inkawhich, M Inkawhich, Y Chen, H Li
arXiv preprint arXiv:1811.11875, 2018
432018
Training SAR-ATR models for reliable operation in open-world environments
NA Inkawhich, EK Davis, MJ Inkawhich, UK Majumder, Y Chen
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2021
382021
Fine-grained out-of-distribution detection with mixup outlier exposure
J Zhang, N Inkawhich, Y Chen, H Li
CoRR, 2021
262021
Advanced Techniques for Robust SAR ATR: Mitigating Noise and Phase Errors
N Inkawhich, E Davis, U Majumder, C Capraro, Y Chen
International Radar Conference (RADAR), 2020
212020
Improving out-of-distribution detection by learning from the deployment environment
N Inkawhich, J Zhang, EK Davis, R Luley, Y Chen
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2022
202022
Finetuning torchvision models
N Inkawhich
Py-Torch tutorials, 2017
202017
Multi-modal aerial view object classification challenge results-PBVS 2023
S Low, O Nina, AD Sappa, E Blasch, N Inkawhich
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
152023
A global model approach to robust few-shot SAR automatic target recognition
N Inkawhich
IEEE Geoscience and Remote Sensing Letters 20, 1-5, 2023
142023
High-performance computing for automatic target recognition in synthetic aperture radar imagery
U Majumder, E Christiansen, Q Wu, N Inkawhich, E Blasch, J Nehrbass
Cyber Sensing 2017 10185, 76-83, 2017
102017
Adversarial attacks on foundational vision models
N Inkawhich, G McDonald, R Luley
arXiv preprint arXiv:2308.14597, 2023
92023
Fine-grain inference on out-of-distribution data with hierarchical classification
R Linderman, J Zhang, N Inkawhich, H Li, Y Chen
Conference on Lifelong Learning Agents, 162-183, 2023
82023
Multi-modal Aerial View Image Challenge: Translation from Synthetic Aperture Radar to Electro-Optical Domain Results-PBVS 2023
S Low, O Nina, AD Sappa, E Blasch, N Inkawhich
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
72023
Can Targeted Adversarial Examples Transfer When the Source and Target Models Have No Label Space Overlap?
N Inkawhich, KJ Liang, J Zhang, H Yang, H Li, Y Chen
Proceedings of the IEEE/CVF International Conference on Computer Vision, 41-50, 2021
62021
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