Kiri L. Wagstaff, Ph.D.
Affiliations: | 2002 | Cornell University, Ithaca, NY, United States |
Area:
Computer ScienceGoogle:
"Kiri Wagstaff"Parents
Sign in to add mentorClaire T. Cardie | grad student | 2002 | Cornell | |
(Intelligent clustering with instance -level constraints.) |
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Publications
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Stillman DE, Bue BD, Wagstaff KL, et al. (2020) Evaluation of wet and dry recurring slope lineae (RSL) formation mechanisms based on quantitative mapping of RSL in Garni Crater, Valles Marineris, Mars Icarus. 335: 113420 |
Lee JH, Wagstaff KL. (2020) Visualizing image content to explain novel image discovery Data Mining and Knowledge Discovery. 1-28 |
Kerner HR, Wagstaff KL, Bue BD, et al. (2020) Comparison of novelty detection methods for multispectral images in rover-based planetary exploration missions Data Mining and Knowledge Discovery. 1-34 |
Kerner HR, Wagstaff KL, Bue BD, et al. (2019) Toward Generalized Change Detection on Planetary Surfaces With Convolutional Autoencoders and Transfer Learning Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 12: 3900-3918 |
Wagstaff KL, Liu GZ. (2018) Automated Classification to Improve the Efficiency of Weeding Library Collections The Journal of Academic Librarianship. 44: 238-247 |
Chien SA, Doubleday J, Thompson DR, et al. (2017) Onboard Autonomy on the Intelligent Payload Experiment CubeSat Mission Journal of Aerospace Information Systems. 14: 307-315 |
Burke-Spolaor S, Trott CM, Brisken WF, et al. (2016) LIMITS on FAST RADIO BURSTS from FOUR YEARS of the V-FASTR EXPERIMENT Astrophysical Journal. 826 |
Wagstaff KL, Tang B, Thompson DR, et al. (2016) A machine learning classifier for fast radio burst detection at the VLBA Publications of the Astronomical Society of the Pacific. 128 |
Hart AF, Cinquini L, Khudikyan SE, et al. (2015) A framework for collaborative review of candidate events in high data rate streams: The v-FASTR experiment as a case study Astronomical Journal. 149 |
Fuchs TJ, Thompson DR, Bue BD, et al. (2015) Enhanced flyby science with onboard computer vision: Tracking and surface feature detection at small bodies Earth and Space Science. 2: 417-434 |