Nathan Inkawhich

According to our database, Nathan Inkawhich authored at least 26 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Out-of-Distribution Detection via Deep Multi-Comprehension Ensemble.

Chenhui Xu, Fuxun Yu, Zirui Xu, Nathan Inkawhich, Xiang Chen

CoRR, 2024

Comprehensive OOD Detection Improvements.

Anish Lakkapragada, Amol Khanna, Edward Raff, Nathan Inkawhich

CoRR, 2024

Tunable Hybrid Proposal Networks for the Open World.

Matthew Inkawhich, Nathan Inkawhich, Hai Li, Yiran Chen

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023

A Global Model Approach to Robust Few-Shot SAR Automatic Target Recognition.

Nathan Inkawhich

IEEE Geosci. Remote. Sens. Lett., 2023

Adversarial Attacks on Foundational Vision Models.

Nathan Inkawhich, Gwendolyn McDonald, Ryan Luley

CoRR, 2023

Establishing baselines and introducing TernaryMixOE for fine-grained out-of-distribution detection.

Noah Fleischmann, Walter D. Bennette, Nathan Inkawhich

CoRR, 2023

SIO: Synthetic In-Distribution Data Benefits Out-of-Distribution Detection.

Jingyang Zhang, Nathan Inkawhich, Randolph Linderman, Ryan Luley, Yiran Chen, Hai Helen Li

CoRR, 2023

Mixture Outlier Exposure: Towards Out-of-Distribution Detection in Fine-grained Environments.

Jingyang Zhang, Nathan Inkawhich, Randolph Linderman, Yiran Chen, Hai Li

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Multi-modal Aerial View Image Challenge: Translation from Synthetic Aperture Radar to Electro-Optical Domain Results - PBVS 2023.

Spencer Low, Oliver Nina, Angel Domingo Sappa, Erik Blasch, Nathan Inkawhich

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Multi-modal Aerial View Object Classification Challenge Results - PBVS 2023.

Spencer Low, Oliver Nina, Angel Domingo Sappa, Erik Blasch, Nathan Inkawhich

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Fine-grain Inference on Out-of-Distribution Data with Hierarchical Classification.

Randolph Linderman, Jingyang Zhang, Nathan Inkawhich, Hai Helen Li, Yiran Chen

Proceedings of the Conference on Lifelong Learning Agents, 2023

2022

Improving Out-of-Distribution Detection by Learning From the Deployment Environment.

Nathan Inkawhich, Jingyang Zhang, Eric K. Davis, Ryan Luley, Yiran Chen

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022

Self-Trained Proposal Networks for the Open World.

Matthew Inkawhich, Nathan Inkawhich, Hai Helen Li, Yiran Chen

CoRR, 2022

The Untapped Potential of Off-the-Shelf Convolutional Neural Networks.

Matthew Inkawhich, Nathan Inkawhich, Eric K. Davis, Hai Li, Yiran Chen

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Multi-modal Aerial View Object Classification Challenge Results - PBVS 2022.

Spencer Low, Oliver Nina, Ángel D. Sappa, Erik Blasch, Nathan Inkawhich

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021

Advancing the Design and Utility of Adversarial Machine Learning Methods.

Nathan Inkawhich

PhD thesis, 2021

Bridging a Gap in SAR-ATR: Training on Fully Synthetic and Testing on Measured Data.

Nathan Inkawhich, Matthew Inkawhich, Eric K. Davis, Uttam K. Majumder, Erin E. Tripp, Chris Capraro, Yiran Chen

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021

Training SAR-ATR Models for Reliable Operation in Open-World Environments.

Nathan Inkawhich, Eric K. Davis, Matthew Inkawhich, Uttam K. Majumder, Yiran Chen

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021

Fine-grained Out-of-Distribution Detection with Mixup Outlier Exposure.

Jingyang Zhang, Nathan Inkawhich, Yiran Chen, Hai Li

CoRR, 2021

Can Targeted Adversarial Examples Transfer When the Source and Target Models Have No Label Space Overlap?

Nathan Inkawhich, Kevin J. Liang, Jingyang Zhang, Huanrui Yang, Hai Li, Yiran Chen

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

NTIRE 2021 Multi-Modal Aerial View Object Classification Challenge.

Jerrick Liu, Nathan Inkawhich, Oliver Nina, Radu Timofte

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020

DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of Ensembles.

Huanrui Yang, Jingyang Zhang, Hongliang Dong, Nathan Inkawhich, Andrew Gardner, Andrew Touchet, Wesley Wilkes, Heath Berry, Hai Li

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability.

Nathan Inkawhich, Kevin J. Liang, Binghui Wang, Matthew Inkawhich, Lawrence Carin, Yiran Chen

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Transferable Perturbations of Deep Feature Distributions.

Nathan Inkawhich, Kevin J. Liang, Lawrence Carin, Yiran Chen

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Feature Space Perturbations Yield More Transferable Adversarial Examples.

Nathan Inkawhich, Wei Wen, Hai (Helen) Li, Yiran Chen

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Adversarial Attacks for Optical Flow-Based Action Recognition Classifiers.

Nathan Inkawhich, Matthew Inkawhich, Yiran Chen, Hai Li

CoRR, 2018