Josh Harguess

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 20

Top Topics

Evaluation Methodology

Satellite Imagery

Quality Assessment

Top Venues

GECCO (Companion)

IEEE Trans. Signal Process.

Publications

Chris M. Ward, Josh Harguess, Julia Tao, Daniel Christman, Paul Spicer, Mike Tan
The AI Security Pyramid of Pain. CoRR (2024)
Josh Harguess, Chris M. Ward
Is the Next Winter Coming for AI? Elements of Making Secure and Robust AI. AIPR (2022)
Mohammad Zarei, Chris M. Ward, Josh Harguess, Marshal Aiken
Adversarial Barrel! An Evaluation of 3D Physical Adversarial Attacks. AIPR (2022)
Ilyas Bankole-Hameed, Arav Parikh, Josh Harguess
Exploring the Effect of Adversarial Attacks on Deep Learning Architectures for X-Ray Data. AIPR (2022)
Marissa Dotter, Sherry Xie, Keith Manville, Josh Harguess, Colin Busho, Mikel Rodriguez
Adversarial Attack Attribution: Discovering Attributable Signals in Adversarial ML Attacks. CoRR (2021)
Michael Threet, Colin Busho, Josh Harguess, Melanie Jutras, Nicole Lape, Sara Leary, Keith Manville, Mike Tan, Chris M. Ward
Physical Adversarial Attacks in Simulated Environments. AIPR (2021)
Emily Holt, Anto Malkastian, Savanna Smith, Chris M. Ward, Josh Harguess
Baseline Evaluation Methodology for Adversarial Patterns on Object Detection Models. AIPR (2021)
Shiri Bendelac, Keith Manville, Josh Harguess, Mikel Rodriguez
A Dynamic Thermal IR Display for Physical Adversarial Attacks. AIPR (2021)
Chris M. Ward, Josh Harguess, Alexander G. Corelli
Leveraging synthetic imagery for collision-at-sea avoidance. CoRR (2019)
Chris M. Ward, Josh Harguess, Cameron Hilton
Ship classification from overhead imagery using synthetic data and domain adaptation. CoRR (2019)
Chris M. Ward, Josh Harguess, Brendan Crabb, Shibin Parameswaran
Image quality assessment for determining efficacy and limitations of Super-Resolution Convolutional Neural Network (SRCNN). CoRR (2019)
Katie Rainey, Josh Harguess
Report on the Second Annual Workshop on Naval Applications of Machine Learning. AI Mag. 39 (4) (2018)
Nancy Ronquillo, Josh Harguess
On Evaluating Video-based Generative Adversarial Networks (GANs). AIPR (2018)
Pedro A. Forero, Scott Shafer, Josh Harguess
Sparsity-Driven Laplacian-Regularized Outlier Identification for Dictionary Learning. IEEE Trans. Signal Process. 65 (14) (2017)
Nancy Ronquillo, Josh Harguess
Informativeness of Degraded Data in Training a Classification System. AIPR (2017)
Josh Harguess, Chris Barngrover, Michael Reese
Optical flow on degraded imagery. AIPR (2016)
Pedro A. Forero, Scott Shafer, Josh Harguess
Structured outlier models for robust dictionary learning. CISS (2015)
Phillip Verbancsics, Josh Harguess
Classifying Maritime Vessels from Satellite Imagery with HyperNEAT. GECCO (Companion) (2015)
Phillip Verbancsics, Josh Harguess
Image Classification Using Generative Neuro Evolution for Deep Learning. WACV (2015)
Phillip Verbancsics, Josh Harguess
Feature Learning HyperNEAT: Evolving Neural Networks to Extract Features for Classification of Maritime Satellite Imagery. IPCAT (2015)
Brian Okorn, Josh Harguess
Ego-Motion Estimation on Range Images Using High-Order Polynomial Expansion. CVPR Workshops (2014)
Phillip Verbancsics, Josh Harguess
Generative NeuroEvolution for Deep Learning. CoRR (2013)
Josh Harguess, Katie Rainey
Are face recognition methods useful for classifying ships? AIPR (2011)
Josh Harguess, Changbo Hu, J. K. Aggarwal
Full-motion recovery from multiple video cameras applied to face tracking and recognition. ICCV Workshops (2011)
Josh Harguess, J. K. Aggarwal
Semantic labeling of track events using time series segmentation and shape analysis. ICIP (2009)
Josh Harguess, Changbo Hu, J. K. Aggarwal
Fusing face recognition from multiple cameras. WACV (2009)
Changbo Hu, Josh Harguess, J. K. Aggarwal
Patch-based face recognition from video. ICIP (2009)
Josh Harguess, Shalini Gupta, Jake K. Aggarwal
3D face recognition with the average-half-face. ICPR (2008)