| Revisiting stereo depth estimation from a sequence-to-sequence perspective with transformers Z Li, X Liu, N Drenkow, A Ding, FX Creighton, RH Taylor, M Unberath Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 274 | 2021 |
| A Systematic Review of Robustness in Deep Learning for Computer Vision: Mind the gap? N Drenkow, N Sani, I Shpitser, M Unberath arXiv preprint arXiv:2112.00639, 2021 | 92 | 2021 |
| A framework for rigorous evaluation of human performance in human and machine learning comparison studies HP Cowley, M Natter, K Gray-Roncal, RE Rhodes, EC Johnson, ... Scientific reports 12 (1), 5444, 2022 | 22 | 2022 |
| The first international competition in machine reconnaissance blind chess RW Gardner, C Lowman, C Richardson, AJ Llorens, J Markowitz, ... NeurIPS 2019 Competition and Demonstration Track, 121-130, 2020 | 12 | 2020 |
| Attack Agnostic Detection of Adversarial Examples via Random Subspace Analysis N Drenkow, N Fendley, P Burlina Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022 | 11* | 2022 |
| Patch attack invariance: How sensitive are patch attacks to 3d pose? M Lennon, N Drenkow, P Burlina Proceedings of the IEEE/CVF International Conference on Computer Vision, 112-121, 2021 | 10 | 2021 |
| Bioimage informatics for big data H Peng, J Zhou, Z Zhou, A Bria, Y Li, DM Kleissas, NG Drenkow, B Long, ... Focus on Bio-Image Informatics, 263-272, 2016 | 10 | 2016 |
| Jacks of all trades, masters of none: addressing distributional shift and obtrusiveness via transparent patch attacks N Fendley, M Lennon, IJ Wang, P Burlina, N Drenkow Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2020 | 8 | 2020 |
| Toward a reproducible, scalable framework for processing large neuroimaging datasets EC Johnson, M Wilt, LM Rodriguez, R Norman-Tenazas, C Rivera, ... BioRxiv, 615161, 2019 | 8 | 2019 |
| On the sins of image synthesis loss for self-supervised depth estimation Z Li, N Drenkow, H Ding, AS Ding, A Lu, FX Creighton, RH Taylor, ... arXiv preprint arXiv:2109.06163, 2021 | 7 | 2021 |
| Toward a scalable framework for reproducible processing of volumetric, nanoscale neuroimaging datasets EC Johnson, M Wilt, LM Rodriguez, R Norman-Tenazas, C Rivera, ... GigaScience 9 (12), giaa147, 2020 | 6 | 2020 |
| Selection of universal features for image classification PA Rodriguez, N Drenkow, D DeMenthon, Z Koterba, K Kauffman, ... IEEE Winter Conference on Applications of Computer Vision, 355-362, 2014 | 4 | 2014 |
| Comparing user experiences in 2D and 3D videoconferencing SS Hemami, FM Ciaramello, SS Chen, NG Drenkow, DY Lee, S Lee, ... 2012 19th IEEE International Conference on Image Processing, 1969-1972, 2012 | 4 | 2012 |
| From generalization to precision: exploring SAM for tool segmentation in surgical environments KJ Oguine, RDS Mukul, N Drenkow, M Unberath Medical Imaging 2024: Image Processing 12926, 7-12, 2024 | 3 | 2024 |
| Circuit summer program: A computational neuroscience outreach experience for high-achieving undergraduates via sponsored research M Encarnacion, C Bishop, J Downs, N Drenkow, JK Matelsky, PK Rivlin, ... 2018 IEEE Integrated STEM Education Conference (ISEC), 45-52, 2018 | 3 | 2018 |
| Benchmarking human performance for visual search of aerial images RE Rhodes, HP Cowley, JG Huang, W Gray-Roncal, BA Wester, ... Frontiers in Psychology 12, 733021, 2021 | 2 | 2021 |
| A sparse null code emerges in deep neural networks BS Robinson, N Drenkow, C Conwell, M Bonner Proceedings of UniReps: the First Workshop on Unifying Representations in …, 2024 | 1 | 2024 |
| Semi-supervised domain transfer for robust maritime satellite image classification PR Emmanuel, CR Ratto, NG Drenkow, JJ Markowitz Artificial Intelligence and Machine Learning for Multi-Domain Operations …, 2023 | 1 | 2023 |
| Exploiting large neuroimaging datasets to create connectome-constrained approaches for more robust, efficient, and adaptable artificial intelligence EC Johnson, BS Robinson, GK Vallabha, J Joyce, JK Matelsky, ... Artificial Intelligence and Machine Learning for Multi-Domain Operations …, 2023 | 1 | 2023 |
| Efficient HVAC Control with Deep Reinforcement Learning and EnergyPlus J Markowitz, N Drenkow ICLR 2023 Workshop on Tackling Climate Change with Machine Learning, 2023 | 1 | 2023 |
