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Autor:
Artur Miroszewski, Jakub Mielczarek, Grzegorz Czelusta, Filip Szczepanek, Bartosz Grabowski, Bertrand Le Saux, Jakub Nalepa
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 7601-7613 (2023)
Support vector machines (SVMs) are well-established classifiers that are effectively deployed in an array of classification tasks. In this article, we consider extending classical SVMs with quantum kernels and applying them to satellite data analysis
Externí odkaz:
https://doaj.org/article/c508406b0fbb47e9a98d99cb262d7619