Paul Tunison

Principal Engineer

Computer Vision

Kitware New York
Clifton Park, NY

10 Years Service at Kitware

B.S. in Computer Science
Union College

Paul Tunison

Paul Tunison is a staff R&D engineer on Kitware’s Computer Vision Team located in Clifton Park, New York. He is involved in software/system design and implementation, as well as AI and machine learning algorithm integration. He also works on system optimization and oversees software integration for some projects.

In addition to his projects, Paul is part of Kitware’s Open Source Committee which aims to increase awareness of open source concepts and strategies within Kitware and in the software R&D industry.

Paul received his bachelor’s degree, magna cum laude, in computer science from Union College. While earning his degree, he performed independent undergraduate research in creating a test-bed system for Natural Language Processing in Second Life. Paul also researched leveraging evolutionary algorithms to adjust game difficulty online, or while a player was actively playing a game. This research culminated in a prototype game titled Genetic Tetris.

Publications

  1. B. Hu, P. Tunison, B. RichardWebster, and A. Hoogs, "Xaitk-Saliency: An Open Source Explainable AI Toolkit for Saliency," Proceedings of the AAAI Conference on Artificial Intelligence, vol. 37, no. 13, pp. 15760-15766, Jun. 2023. [URL]
  2. B. Hu, P. Tunison, B. Vasu, N. Menon, R. Collins, and A. Hoogs, "XAITK: The explainable AI toolkit," Applied AI Letters, Oct. 2021. [URL]
  3. M. Brown, K. Fieldhouse, E. Swears, P. Tunison, A. Romlein, and A. Hoogs, "Multi-Modal Detection Fusion on a Mobile UGV for Wide-Area, Long-Range Surveillance," in 2019 IEEE Winter Conference on Applications of Computer Vision (WACV), 2019. [URL]
  4. D. Chittajallu, B. Dong, P. Tunison, R. Collins, K. Wells, J. Fleshman, G. Sankaranarayanan, S. Schwaitzberg, L. Cavuoto, and A. Enquobahrie, "XAI-CBIR: Explainable AI System for Content based Retrieval of Video Frames from Minimally Invasive Surgery Videos," in 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), 2019. [URL]
  5. C. Funk, J. Crall, W. Hicks, C. Law, P. Tunison, R. Blue, A. Hoogs, T. Rovito, and A. Maltenfort, "WEFT Feature Detection and Mensuration for Airplane Classification in Satellite Imagery," in MSS National Symposium on Sensor and Data Fusion, 2019.
  6. D. Chittajallu, A. Basharat, P. Tunison, S. Horvath, K. Wells, S. Leeds, J. Fleshman, G. Sankaranarayanan, and A. Enquobahrie, "Content-based retrieval of video segments from minimally invasive surgery videos using deep convolutional video descriptors and iterative query refinement," in Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 2019.
  7. C. Law, R. Blue, D. Stoup, P. Tunison, A. Hoogs, B. Vasu, J. Van Cor, J. Kerekes, A. Savakis, T. Rovito, C. Stansifer, and S. Thomas, "Deep Learning for Object Detection and Classification in Satellite Imagery," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2018.
  8. J. Crall, J. Becker, P. Tunison, M. Dawkins, A. Basharat, R. Blue, M. Turek, and A. Hoogs, "Deep Learning for Small Object Detection in Satellite Infrared Imagery," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2018.
  9. M. Brown, K. Fieldhouse, E. Swears, P. Tunison, A. Romlein, and A. Hoogs, "Multi-Modal Detection Fusion on Mobile UGV for Squad-Level Threat Alerting," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2018.
  10. A. Basharat, P. Tunison, and A. Hoogs, "Rapid Learning of Maritime Scenes Through Query Refinement," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2018.
  11. C. Law, J. Parham, M. Dawkins, P. Tunison, D. Stoup, R. Blue, K. Fieldhouse, M. Turek, A. Hoogs, S. Han, A. Farafard, J. Kerekes, E. Lentilucci, M. Gartley, T. Savakis, T. Rovito, S. Thomas, and C. Stansifer, "Deep learning for object detection and object-based change detection in satellite imagery," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2017.
  12. M. Leotta, E. Smith, M. Dawkins, and P. Tunison, "Open source structure-from-motion for aerial video," in Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2016. [URL]
  13. P. Tunison, M. Turek, and A. Hoogs, "Functional scene element modeling for ISR data," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2016.
  14. Z. Sun, J. Baumes, P. Tunison, M. Turek, and A. Hoogs, "Tattoo detection and localization using region-based deep learning," in Proceedings of the IEEE International Conference on Pattern Recognition, 2016. [URL]
  15. M. Turek, A. Basharat, K. Fieldhouse, P. Tunison, D. Stoup, C. Atkins, and A. Hoogs, "Real-time, full-frame wide area motion imagery analytics," in Proceedings of the MSS National Symposium on Passive Sensors, 2015.
  16. M. Leotta, P. Tunison, E. Smith, and M. Dawkins, "MAP-Tk: Motion imagery Aerial Photogrammetry Toolkit," in Proceedings of the MSS National Symposium on Passive Sensors, 2015.
  17. K. Fieldhouse, M. Leotta, A. Basharat, R. Blue, D. Stoup, C. Atkins, L. Sherrill, B. Boeckel, P. Tunison, J. Becker, M. Dawkins, M. Woehlke, R. Collins, M. Turek, and A. Hoogs, "KWIVER: An open source cross-platform video exploitation framework," in Proceedings of the IEEE Applied Imagery Pattern Recognition Workshop, 2014. [URL]
  18. A. Basharat, M. Turek, Y. Xu, C. Atkins, D. Stoup, K. Fieldhouse, P. Tunison, and A. Hoogs, "Real-time multi-target tracking at 210 megapixels/second in Wide Area Motion Imagery," in Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2014. [URL]

Bibliography generated 2023-12-04-16:40:27 (6744)