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Titlebook: Machine Learning and Internet of Things for Societal Issues; Ch. Satyanarayana,Xiao-Zhi Gao,Naresh Babu Muppala Book 2022 The Editor(s) (i

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书目名称Machine Learning and Internet of Things for Societal Issues
编辑Ch. Satyanarayana,Xiao-Zhi Gao,Naresh Babu Muppala
视频video
概述Highlights recent advance in Machine Learning and IoT and their applications to solve various societal issues/problems.Presents contributions from leading experts in industry and academia.Includes int
丛书名称Advanced Technologies and Societal Change
图书封面Titlebook: Machine Learning and Internet of Things for Societal Issues;  Ch. Satyanarayana,Xiao-Zhi Gao,Naresh Babu Muppala Book 2022 The Editor(s) (i
描述.This book highlights recent advance in the area of Machine Learning and IoT, and their applications to solve societal issues/problems or useful for various users in the society. It is known that many smart devices are interconnected and the data generated is being analyzed and processed with machine learning models for prediction, classification, etc., to solve human needs in various sectors like health, road safety, agriculture, and education. This contributed book puts together chapters concerning the use of intelligent techniques in various aspects related to the IoT domain from protocols to applications, to give the reader an up-to-date picture of the state-of-the-art on the connection between computational intelligence, machine learning, and IoT..
出版日期Book 2022
关键词Deep Learning; Smart agriculture; Speech recognition; Object detection; Object segmentation; Satellite im
版次1
doihttps://doi.org/10.1007/978-981-16-5090-1
isbn_softcover978-981-16-5092-5
isbn_ebook978-981-16-5090-1Series ISSN 2191-6853 Series E-ISSN 2191-6861
issn_series 2191-6853
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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Early Prediction of COVID-19 Using Modified Convolutional Neural Networks,networks (DRN) with pre-training techniques for classifying X-ray chest images into three broad collection, viz., normal or negative, pneumonia positive and COVID-19 positive, based on two other open-source data sets. This fivefold research work is based on data sets consisting of 980 X-ray chest im
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