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 Fuzzy Lattice Neural Model and Fuzzy Equivalance Relation Model. Classification and Clustering
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Fuzzy Lattice Neural Model and Fuzzy Equivalance Relation Model. Classification and Clustering

автор KALAMANI D. издательство Книга по Требованию Математический анализ. Кратные и криволинейные интегралы. Задачи, решения
Cтраниц 132        мягкая обложка       
Аннотация:Computer vision, unlike humans, still has not fully acquired the ability to categorise a person' s age group from an image of the person' s face. Successful gender and age classification could be used to boot the performance of face recognition system. Then, the fuzzy lattice neural model is applied to segment an aerial gray scale image. The concept of fuzzy lattice neural model is introduced and is applied to classify the age group of a person from the gray scale facial image. Fuzzy models have been used and analysed in this work to achieve the desired results. Next, the fuzzy equivalence relation model is constructed and is used to classify the age group of a person. Finally, fuzzy lattice neural model is compared with other models like fuzzy equivalence relation model, Kohenen' s clustering neural model that are used for classification. The hybridization of the technologies is demonstrated on architectures such as Neuro-fuzzy systems. This book should be of interest to researchers and technologists desirous of applying FLN technology to their respective fields of work.
Автор: KALAMANI D.
Издательство: Книга по Требованию
Год:2011
Цена:
2260 руб
Нет в наличии
Поиск: Fuzzy Lattice Neural Model and Fuzzy Equivalance Relation Model. Classification and Clustering
НОВЫЙ ГОД СИМВОЛ 2013 ГОДАУКРАШЕНИЯ
КАРНАВАЛ НА НОВЫЙ ГОД РАСПРОДАЖА
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За основу берется интерфейс Fac DAOI eface, задающий принципы работы с фактами. Его необходимо реализовать для всех типов источников данных, которые будут подключены к системе. При реализации данного интерфейса в случае, когда некоторые источники данных имеют общие черты, следует использовать empla e Me hod для увеличения степени повторного использования кода. Рис. 2.6 Доступ к фактам 2.4. Пакет ядра Пакет server.ker el на рис. 2.7 представляет собой набор заводов Fac DAOFac ory, Me aFac ory и Securi yFac ory, управляющих моделями пакетов model.fac , model.me a и model.securi y, которые были описаны выше. Классы Abs rac Me aSource и Abs rac Fac Source в своей работе используют безопасность, т.е. пользуются услугами Securi yFac ory. Основная функциональная нагрузка ядра ложится на классы Abs rac Fac Source, Abs rac Me aSource и Abs rac Securi ySource, но процесс управления объектами моделей model.fac , model.me a и model.securi y делегируется классам Fac DAOFac ory, Me aFac ory и Securi yFac ory с использованием шаблона Adap er. Рис. 2.7 Ядро системы 2.5. Пакеты источников метамодели, фактов и безопасности Пакет source.me a на рис. 2.8 представляет собой интерфейс Me aSourceI erface с поддерживающим его заводом по шаблону Fac ory Me hod, который предоставляет клиентскому приложению Proxy-объект этого интерфейса по шаблону Proxy.
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