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MACHINE LEARNING ALGORITHMS: OBJECT IDENTIFICATION BASED ON FEATURE EXTRACTION FROM MULTISPECTRAL SATELLITE IMAGES USING PRINCIPAL COMPONENT ANALYSIS - G. Sreenivasulu,Mundluru Dharani

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2023-11-24
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Remote sensing is immensely useful for gathering data from Earth-surface objects without coming into direct contact with them. Multi-spectral satellite images are essential for data analysis in the fields of agriculture, regional planning, geology, meteorology, forestry, landscape, biodiversity conservation. Enhancement is the best method for extracting more information from a large dataset. The information ... Pilns apraksts

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Remote sensing is immensely useful for gathering data from Earth-surface objects without coming into direct contact with them. Multi-spectral satellite images are essential for data analysis in the fields of agriculture, regional planning, geology, meteorology, forestry, landscape, biodiversity conservation. Enhancement is the best method for extracting more information from a large dataset. The information increases the number of pixels that can effectively represent the image's information and display its spectral features. These values are maintaining the trade-off balance between spatial and spectral values with dimensional reduction technique and Machine Learning algorithms.

Vairāk informācijas

Autors G. Sreenivasulu, Mundluru Dharani
Izdevējs LAP LAMBERT Academic Publishing
Izlaides gads 2023
Vāka tips Mīkstais vāks
EAN 9786206142188
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