Nathan Drenkow

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 22

Top Topics

Attack Detection

Depth Estimation

Top Venues

ECCV Workshops (1)

Publications

Kanyifeechukwu Jane Oguine, Roger D. Soberanis-Mukul, Nathan Drenkow, Mathias Unberath
From Generalization to Precision: Exploring SAM for Tool Segmentation in Surgical Environments. CoRR (2024)
Nathan Drenkow, Mathias Unberath
RobustCLEVR: A Benchmark and Framework for Evaluating Robustness in Object-centric Learning. WACV (2024)
Mitchell Pavlak, Nathan Drenkow, Nicholas Petrick, Mohammad Mehdi Farhangi, Mathias Unberath
Data AUDIT: Identifying Attribute Utility- and Detectability-Induced Bias in Task Models. CoRR (2023)
Erik C. Johnson, Brian S. Robinson, Gautam K. Vallabha, Justin Joyce, Jordan K. Matelsky, Raphael Norman-Tenazas, Isaac Western, Marisel Villafañe-Delgado, Martha Cervantes, Michael S. Robinette, Arun V. Reddy, Lindsey Kitchell, Patricia K. Rivlin, Elizabeth Perez Reilly, Nathan Drenkow, Matthew J. Roos, I-Jeng Wang, Brock A. Wester, William R. Gray Roncal, Joan A. Hoffmann
Exploiting Large Neuroimaging Datasets to Create Connectome-Constrained Approaches for more Robust, Efficient, and Adaptable Artificial Intelligence. CoRR (2023)
Brian S. Robinson, Nathan Drenkow, Colin Conwell, Michael F. Bonner
A sparse null code emerges in deep neural networks. UniReps (2023)
Nathan Drenkow, Max Lennon, I-Jeng Wang, Philippe Burlina
Do Adaptive Active Attacks Pose Greater Risk Than Static Attacks? WACV (2023)
Mitchell Pavlak, Nathan Drenkow, Nicholas Petrick, Mohammad Mehdi Farhangi, Mathias Unberath
Data AUDIT: Identifying Attribute Utility- and Detectability-Induced Bias in Task Models. MICCAI (3) (2023)
Nathan Drenkow, Mathias Unberath
RobustCLEVR: A Benchmark and Framework for Evaluating Robustness in Object-centric Learning. CoRR (2023)
Nathan Drenkow, Neil Fendley, Philippe Burlina
Attack Agnostic Detection of Adversarial Examples via Random Subspace Analysis. WACV (2022)
Nathan Drenkow, Alvin Tan, Chace Ashcraft, Kiran Karra
Context-Adaptive Deep Neural Networks via Bridge-Mode Connectivity. CoRR (2022)
Max Lennon, Nathan Drenkow, Philippe Burlina
Patch Attack Invariance: How Sensitive are Patch Attacks to 3D Pose? CoRR (2021)
Nathan Drenkow, Numair Sani, Ilya Shpitser, Mathias Unberath
Robustness in Deep Learning for Computer Vision: Mind the gap? CoRR (2021)
Nathan Drenkow, Philippe Burlina, Neil Fendley, Onyekachi Odoemene, Jared Markowitz
Addressing Visual Search in Open and Closed Set Settings. CVPR Workshops (2021)
Zhaoshuo Li, Nathan Drenkow, Hao Ding, Andy S. Ding, Alexander Lu, Francis X. Creighton, Russell H. Taylor, Mathias Unberath
On the Sins of Image Synthesis Loss for Self-supervised Depth Estimation. CoRR (2021)
Max Lennon, Nathan Drenkow, Philippe Burlina
Patch Attack Invariance: How Sensitive are Patch Attacks to 3D Pose? ICCVW (2021)
Zhaoshuo Li, Xingtong Liu, Nathan Drenkow, Andy S. Ding, Francis X. Creighton, Russell H. Taylor, Mathias Unberath
Revisiting Stereo Depth Estimation From a Sequence-to-Sequence Perspective with Transformers. ICCV (2021)
Neil Fendley, Max Lennon, I-Jeng Wang, Philippe Burlina, Nathan Drenkow
Jacks of All Trades, Masters Of None: Addressing Distributional Shift and Obtrusiveness via Transparent Patch Attacks. CoRR (2020)
Nathan Drenkow, Justin Joyce, Jordan Matelsky, Jennifer Heiko, Reem Larabi, Brock A. Wester, Dean Kleissas, William R. Gray Roncal
Leveraging Tools from Autonomous Navigation for Rapid, Robust Neuron Connectivity. MICCAI (5) (2020)
Nathan Drenkow, Neil Fendley, Philippe Burlina
Random Projections for Adversarial Attack Detection. CoRR (2020)
Nathan Drenkow, Philippe Burlina, Neil Fendley, Kachi Odoemene, Jared Markowitz
Objectness-Guided Open Set Visual Search and Closed Set Detection. CoRR (2020)
Neil Fendley, Max Lennon, I-Jeng Wang, Philippe Burlina, Nathan Drenkow
Jacks of All Trades, Masters of None: Addressing Distributional Shift and Obtrusiveness via Transparent Patch Attacks. ECCV Workshops (1) (2020)
Ryan W. Gardner, Corey Lowman, Casey Richardson, Ashley J. Llorens, Jared Markowitz, Nathan Drenkow, Andrew Newman, Gregory Clark, Gino Perrotta, Robert Perrotta, Timothy Highley, Vlad Shcherbina, William Bernadoni, Mark Jordan, Asen Asenov
The First International Competition in Machine Reconnaissance Blind Chess. NeurIPS (Competition and Demos) (2019)
Pedro A. Rodriguez, Nathan Drenkow, Daniel DeMenthon, Zachary H. Koterba, Kathleen Kauffman, Duane Cornish, Bart L. Paulhamus, R. Jacob Vogelstein
Selection of universal features for image classification. WACV (2014)
Nathan Drenkow, Philippe Burlina, I-Jeng Wang, Daniel DeMenthon, Craig Carmen
A practical test set bound for rank learning. MLSP (2013)