Machine learning classifiers &Classifier ensample: improvement of land cover classification - Brossura

Taha, Lamyaa; Ibrahim, Rania; Mandouh, Asmaa

 
9786206845867: Machine learning classifiers &Classifier ensample: improvement of land cover classification
Brossura
ISBN 10: 6206845869 ISBN 13: 9786206845867
Casa editrice: LAP LAMBERT Academic Publishing, 2023

Sinossi

There are an emergent machine learning(ML) algorithms to classify land-cover and land-use. In this book we focus on the relatively mature methods (seven methods) support vector (SVM) machines, decision trees (DTs), artificial neural networks, k-nearest neighbours (k-NN), naïve Bayes, Boosting and Random forest (RF).Accurate and timely collection of urban land use and land cover information is crucial for many aspects of urban development and environment protection.Accurate land covers classification is challenging. Improving land cover classification is a hot topic. It is needed for many applications such as land use land cover mapping environmental monitoring, natural resource management, urban planning, and management and change detection. Then a number of ensample methods were studied to combine various classifiers.

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Editore
LAP LAMBERT Academic Publishing
Data di pubblicazione
2023
Lingua
Inglese
ISBN 10 
6206845869
ISBN 13 
9786206845867
Rilegatura
Copertina flessibile
Numero di pagine
52
Contatto del produttore
non disponibile
Persona responsabile
KreGa Onlinehandel GmbH
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