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Leonhard Held,Daniel Sabanés Bovéan inevitable platform in all engineering domains. The need for sophisticated and ambient environments controlled by tech has resulted in an exponential growth of automation and artificial intellig978-1-4842-8107-9978-1-4842-8108-6Series ISSN 2948-2542 Series E-ISSN 2948-2550
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1431-8776 ce” has been expanded to include new material on Markov models for time series analysis. It also features a comprehensive appendix covering the prerequisites in probability theory, matrix algebra, mathematical 978-3-662-60794-7978-3-662-60792-3Series ISSN 1431-8776 Series E-ISSN 2197-5671
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Leonhard Held,Daniel Sabanés Bové healthcare integration components. The chapter presents seamless applications dispensed by CloudIoT platform and contemplates discussion on factors driving CloudIoT health integration. The chapter also presents a conceptual architectural framework for healthcare monitoring system that considers a r
灿烂
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Leonhard Held,Daniel Sabanés Bovéance and enhance their feature. Healthcare assistance supports the continual therapy, observance of victims at intervals the unit, and offers around the timekeeper help and makes sure that the encircling setting does not hinder their treatment and observance. Recently, an IoT (Internet of Things) po
颂扬国家
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BUOY
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Leonhard Held,Daniel Sabanés Bovéthe efficiency of decision-making by analyzing harvest statistics. Further, it explores climate-smart methods, known as smart agriculture, that have been adopted by a number of Indian farmers..978-981-15-0665-9978-981-15-0663-5Series ISSN 2197-6503 Series E-ISSN 2197-6511
Arroyo
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Leonhard Held,Daniel Sabanés Bové deep learning with the emphasis on their application for AI implementation in the field of agri-food material handling. Popular ML algorithms viz., support vector machine (SVM), K-nearest neighbor (KNN), artificial neural networks (ANN), decision trees, and convolutional neural networks (CNN) are d
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Crumple
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Textbook 2020Latest editiont and Bayesian perspectives. This revised edition of the book “Applied Statistical Inference” has been expanded to include new material on Markov models for time series analysis. It also features a comprehensive appendix covering the prerequisites in probability theory, matrix algebra, mathematical