Отправить статью по E-mail Nonparametric Algorithms for Estimating the States of Natural Objects
- Авторы: Lapko A.V.1,2, Lapko V.A.1,2
-
Учреждения:
- Institute of Computational Modeling, Siberian Branch
- Reshetnev Siberian State University of Science and Technology
- Выпуск: Том 54, № 5 (2018)
- Страницы: 451-456
- Раздел: Analysis and Synthesis of Signals and Images
- URL: https://journals.rcsi.science/8756-6990/article/view/212557
- DOI: https://doi.org/10.3103/S8756699018050047
- ID: 212557
Цитировать
Открытый доступ
Доступ предоставлен
Только для подписчиков
Аннотация
Modifications of a nonparametric pattern recognition algorithm corresponding to the maximum likelihood criterion with additional decision functions are considered. The synthesis of the proposed algorithms is based on the analysis of the ratios of the estimates of the probability density distributions of random variables in classes and their functionals with input thresholds. The choice of the thresholds is determined by specific features of the classification problem. The results obtained are applied for assessing the states of forest tracts on the basis of remote sensing data.
Об авторах
A. Lapko
Institute of Computational Modeling, Siberian Branch; Reshetnev Siberian State University of Science and Technology
Автор, ответственный за переписку.
Email: lapko@icm.krasn.ru
Россия, Academgorodok-50, 44, Krasnoyarsk, 660036; pr. Krasnoyarskii rabochii 31, Krasnoyarsk, 660037
V. Lapko
Institute of Computational Modeling, Siberian Branch; Reshetnev Siberian State University of Science and Technology
Email: lapko@icm.krasn.ru
Россия, Academgorodok-50, 44, Krasnoyarsk, 660036; pr. Krasnoyarskii rabochii 31, Krasnoyarsk, 660037
Дополнительные файлы
