
Machine Learning and IoT for Intelligent Systems and Smart Applications
Description
Alles über E-Books | Antworten auf Fragen rund um E-Books, Kopierschutz und Dateiformate finden Sie in unserem Info- & Hilfebereich.
Features:
Focuses on algorithmic and practical parts of the artificial intelligence approaches in IoT applications.
Discusses supervised and unsupervised machine learning for IoT data and devices.
Presents an overview of the different algorithms related to Machine learning and IoT.
Covers practical case studies on industrial and smart home automation.
Includes implementation of AI from case studies in personal and industrial IoT.
This book aims at Researchers and Graduate students in Computer Engineering, Networking Communications, Information Science Engineering, and Electrical Engineering.
More details
Other editions
Additional editions


Persons
Dr. M Vinoth Kumar, obtained his Bachelor's degree in Computer Science and Engineering from Periyar University, Salem, Tamilnadu, India. He obtained his Master's degree in Computer Science and Engineering and PhD in Computer Science majoring in Agent Programming from Anna University, Chennai, Tamilnadu, India. Currently, he is an Associate professor at the Faculty of Information Science and Engineering, RV Institute of Technology and Management, Bengaluru, Karnataka, India. His specializations includes Artificial Intelligence, Machine learning and Big Data Computing. His current research interests are convolutional neural network and medical image processing. He has published 45 research papers in reputed national, International journals and conferences. He has filed 6 innovative patents and 1 patent is granted by Indian patent office. He is the reviewer and editorial member in Indexed national and International Journals. He is the life member of Computer Society of India(CSI), Indian Science Congress Association(ISCA) and associate member of Institute of Engineers(India), Indian Society of Technical Education(ISTE).
Dr. R. Umamaheswari, currently working as Assistant Professor in Department of Electronics & Instrumentation Engineering at SRM Valliammai Engineering College, Kattankulathur, Tamilnadu, India. She has completed her Ph. D in the field of wireless communication in the year 2017 from Anna University. She completed her Masters in VLSI Design Engineering (2011) from Anna University and Bachelors in Electronics and Instrumentation Engineering (2004) from Madras University. She received gold medal in her Master's Degree. She has more than 10 years of teaching experience. She specializes herself in the core area of soft computing techniques. She is an innovative person with deep knowledge in Artificial Intelligence, Neuro-fuzzy systems and IoT. She has published more than 25 research articles in national and international journals. She has published three text books for Basic electrical, electronics and instrumentation engineering for second semester anna university syllabus. She has filed three patents in India. She has organized guest lecture, seminars, faculty development programme under the banner of All India Council of Technical Education (AICTE). She delivered guest lecture in various institutions and also shared various chair-positions in conferences, seminars. She is Life Member of professional societies like ISTE, ISC, CSI, IAENG.
Content
Chapter 2 Machine Learning based Microstrip Antenna Design in Wireless Communications
Chapter 3 LCL-T Filter Based Analysis of Two Stage Single Phase Grid Connected Module with Intelligent FANN Controllers
Chapter 4 Motion Vector Analysis Using Machine Learning Models to Identify Lung Damages for COVID-19 Patients
Chapter 5 Enhanced Effective Generative Adversarial Networks Based LRSD and SP Learned Dictionaries with Amplifying CS
Chapter 6 Deep Learning Based Parkinson's Disease Prediction System
Chapter 7 Non-Uniform Data Reduction Technique with Edge Preservation to Improve Diagnostic Visualization of Medical Images
Chapter 8 A Critical Study on Genetically Engineered Bioweapons and Computer-Based Techniques as Counter Measure
Chapter 9 An Automated Hybrid Transfer Learning system for Detection and Segmentation of Tumor in MRI Brain Images with UNet and VGG-19 Network
Chapter 10 Deep Learning-Computer Aided Melanoma Detection Using Transfer Learning
Chapter 11 Development of an Agent-based Interactive Tutoring System for Online Teaching in School using Classter
Chapter 12 Fusion of Datamining and Artificial Intelligence in Prediction of Hazardous Road Accidents
System requirements
File format: ePUB
Copy protection: Adobe-DRM (Digital Rights Management)
System requirements:
- Computer (Windows; MacOS X; Linux): Install the free reader Adobe Digital Editions prior to download (see eBook Help).
- Tablet/smartphone (Android; iOS): Install the free app Adobe Digital Editions or the app PocketBook before downloading (see eBook Help).
- E-reader: Bookeen, Kobo, Pocketbook, Sony, Tolino and many more (not Kindle).
The file format ePub works well for novels and non-fiction books – i.e., „flowing” text without complex layout. On an e-reader or smartphone, line and page breaks automatically adjust to fit the small displays.
This eBook uses Adobe-DRM, a „hard” copy protection. If the necessary requirements are not met, unfortunately you will not be able to open the eBook. You will therefore need to prepare your reading hardware before downloading.
Please note: We strongly recommend that you authorise using your personal Adobe ID after installation of any reading software.
For more information, see our ebook Help page.