image clustering classification using de segu praveena (5 resultados)

Taschenbuch. Condición: Neu. Neuware -This research work focused on the satellite image clustering by developing some numerical algorithms to analyze the satellite images captured by satellites. it is aimed to enhance the classification accuracy by two proposed algorithms. Each approach goes through three phrases i.e preprocessing, segmentation and classification. these approaches show optimal results under observing condition, dynamic variation in regional details or noise effect degrades its performance.Books on Demand GmbH, Überseering 33, 22297 Hamburg 116 pp. Englisch.

Paperback. Condición: Brand New. 116 pages. 8.66x5.91x0.27 inches. In Stock.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This research work focused on the satellite image clustering by developing some numerical algorithms to analyze the satellite images captured by satellites. it is aimed to enhance the classification accuracy by two proposed algorithms. Each approach goes through three phrases i.e preprocessing, segmentation and classification. these approaches show optimal results under observing condition, dynamic variation in regional details or noise effect degrades its performance. 116 pp. Englisch.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Segu PraveenaShe completed her B.Tech from RGMCET(Rajeev Gandhi Memorial College of Engineering and Technology),Nandyal, A.P and PG,Ph.D from JNTUH, Hyderabad in the years 2006,2016 respectively. Presently working at MGIT as Asst.Pro.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This research work focused on the satellite image clustering by developing some numerical algorithms to analyze the satellite images captured by satellites. it is aimed to enhance the classification accuracy by two proposed algorithms. Each approach goes through three phrases i.e preprocessing, segmentation and classification. these approaches show optimal results under observing condition, dynamic variation in regional details or noise effect degrades its performance.