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pro vyhledávání: '"Sisti, Sean P."'
Given a black-box classification model and an unlabeled evaluation dataset from some application domain, efficient strategies need to be developed to evaluate the model. Random sampling allows a user to estimate metrics like accuracy, precision, and
Externí odkaz:
http://arxiv.org/abs/2102.12844
Given a deep neural network image classification model that we treat as a black box, and an unlabeled evaluation dataset, we develop an efficient strategy by which the classifier can be evaluated. Randomly sampling and labeling instances from an unla
Externí odkaz:
http://arxiv.org/abs/2006.16055
Autor:
Hammoud, Riad I., Overman, Timothy L., Mahalanobis, Abhijit, Jaskie, Kristen, Sisti, Sean, Bennette, Walter
Publikováno v:
Proceedings of SPIE; May 2022, Vol. 12096 Issue: 1 p120960E-120960E-8, 1088649p
Efficient fine-grained automatic target recognition through active learning for defense applications
Autor:
Schwartz, Peter J., Jensen, Benjamin, Hohil, Myron E., Thorp, Claire A., Sisti, Sean P., Browne, Lesrene A., Schwartz, Casey, Inkawhich, Nathan, Bennette, Walter
Publikováno v:
Proceedings of SPIE; June 2024, Vol. 13051 Issue: 1 p1305111-1305111-8