Name: Satellite Image Analysis: Clustering and Classification (Springerbriefs in Applied Sciences and Technology) (en Inglés)
SKU: 51502160
Price: 65.37 USD
Availability: InStock
Author: Surekha Borra

portada Satellite Image Analysis: Clustering and Classification (Springerbriefs in Applied Sciences and Technology) (en Inglés)

Satellite Image Analysis: Clustering and Classification (Springerbriefs in Applied Sciences and Technology) (en Inglés)

Formato

Libro Físico

Editorial

Springer

Autor

Surekha Borra

Año

2019

Idioma

Inglés

N° páginas

116

Encuadernación

Tapa Blanda

ISBN13

9789811364235

N° edición

Categorías

Aplicaciones gráficas y multimedia

Satellite Image Analysis: Clustering and Classification (Springerbriefs in Applied Sciences and Technology) (en Inglés)

Surekha Borra (Autor) · Springer · Tapa Blanda

Libro Nuevo Importado

Envío: 20 a 27 días háb.

$ 130.74$ 65.37

-50%

Costos de importación incluídos en el precio ✅

Libro Nuevo

Quedan más de 100 unidades

$ 65.37

Llega entre el 21 Sep y el 02 Oct a Quito, Pichincha. Seleccionar ubicación

Agregar a lista de deseos

Reseña del libro "Satellite Image Analysis: Clustering and Classification (Springerbriefs in Applied Sciences and Technology) (en Inglés)"

Thanks to recent advances in sensors, communication and satellite technology, data storage, processing and networking capabilities, satellite image acquisition and mining are now on the rise. In turn, satellite images play a vital role in providing essential geographical information. Highly accurate automatic classification and decision support systems can facilitate the efforts of data analysts, reduce human error, and allow the rapid and rigorous analysis of land use and land cover information. Integrating Machine Learning (ML) technology with the human visual psychometric can help meet geologists’ demands for more efficient and higher-quality classification in real time. This book introduces readers to key concepts, methods and models for satellite image analysis; highlights state-of-the-art classification and clustering techniques; discusses recent developments and remaining challenges; and addresses various applications, making it a valuable asset for engineers, data analysts and researchers in the fields of geographic information systems and remote sensing engineering.