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Emerging Trends, Techniques, and Applications in Geospatial Data Science

Name: Emerging Trends, Techniques, and Applications in Geospatial Data Science
Brand: IGI Global
SKU: 9781668473207
Price: 215.64 EUR
Availability: InStock

Autor: Loveleen Gaur

Jazyk:

Väzba: Brožovaná

Vydavateľ: IGI Global

Dostupnosť: Skladom u dodávateľa

Odosielame za 10-18 dní

215.64 €

With the emergence of smart technology and automated systems in today's world, big data is being inc...

Informácie o knihe

Autor

Loveleen Gaur

Jazyk

Angličtina

Väzba

Kniha - Brožovaná

Vydalo

2023

Stránok

332

EAN

9781668473207

ISBN

1668473208

Enbook ID

43323346

Vydavateľ

IGI Global

Hmotnosť

838

Rozmery

216 x 280 x 18

Kompletný popis

With the emergence of smart technology and automated systems in today's world, big data is being incorporated into many applications. Trends in data can be detected and objects can be tracked based on the real-time data that is utilized in everyday life. These connected sensor devices and objects will provide a large amount of data that is to be analyzed quickly, as it can accelerate the transformation of smart technology. The accuracy of prediction of artificial intelligence (AI) systems is drastically increasing by using machine learning and other probability and statistical approaches. Big data and geospatial data help to solve complex issues and play a vital role in future applications. Emerging Trends, Techniques, and Applications in Geospatial Data Science provides an overview of the basic concepts of data science, related tools and technologies, and algorithms for managing the relevant challenges in real-time application domains. The book covers a detailed description for readers with practical ideas using AI, the internet of things (IoT), and machine learning to deal with the analysis, modeling, and predictions from big data. Covering topics such as field spectra, high-resolution sensing imagery, and spatiotemporal data engineering, this premier reference source is an excellent resource for data scientists, computer and IT professionals, managers, mathematicians and statisticians, health professionals, technology developers, students and educators of higher education, librarians, researchers, and academicians.

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