Fahimuddin Shaik – författare

The book highlights the importance of using machine learning algorithms for smart intelligent devices, security and privacy issues of the Internet of Things.Features: Discusses comprehensively topics such as sensor data collection, data preprocessing, feature extraction, and model training Offers simplified explanations of algorithms like neural networks, decision trees, and clustering techniques, making them accessible to readers with limited technical background Showcases practical insights by presenting real-world applications of the Internet of Things, and machine learning in domains such as smart homes, healthcare, transportation, and manufacturing Covers issues such as data quality, model overfitting, security vulnerabilities, and scalability. Includes tutorials on setting up Internet of Things devices, collecting and preprocessing data, and building machine learning models The text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.

The book highlights the importance of using machine learning algorithms for smart intelligent devices, security and privacy issues of the Internet of Things.Features: Discusses comprehensively topics such as sensor data collection, data preprocessing, feature extraction, and model training Offers simplified explanations of algorithms like neural networks, decision trees, and clustering techniques, making them accessible to readers with limited technical background Showcases practical insights by presenting real-world applications of the Internet of Things, and machine learning in domains such as smart homes, healthcare, transportation, and manufacturing Covers issues such as data quality, model overfitting, security vulnerabilities, and scalability. Includes tutorials on setting up Internet of Things devices, collecting and preprocessing data, and building machine learning models The text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.

The book highlights the importance of using machine learning algorithms for smart intelligent devices, security and privacy issues of the Internet of Things.Features:Discusses comprehensively topics such as sensor data collection, data preprocessing, feature extraction, and model trainingOffers simplified explanations of algorithms like neural networks, decision trees, and clustering techniques, making them accessible to readers with limited technical backgroundShowcases practical insights by presenting real-world applications of the Internet of Things, and machine learning in domains such as smart homes, healthcare, transportation, and manufacturingCovers issues such as data quality, model overfitting, security vulnerabilities, and scalability. Includes tutorials on setting up Internet of Things devices, collecting and preprocessing data, and building machine learning modelsThe text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.

This book highlights recentfindings on and analysesconducted on signalsand images in the area of medicine. The experimental investigations involve a variety of signalsand images and theirmethodologies range from very basic to sophisticated methods. The bookexplains how signal and image processing methods can be used to detect andforecast abnormalities in an easy-to-followmanner, offering a valuable resource for researchers, engineers,physicians and bioinformatics researchers alike.

This book highlights recentfindings on and analysesconducted on signalsand images in the area of medicine. The experimental investigations involve a variety of signalsand images and theirmethodologies range from very basic to sophisticated methods. The bookexplains how signal and image processing methods can be used to detect andforecast abnormalities in an easy-to-followmanner, offering a valuable resource for researchers, engineers,physicians and bioinformatics researchers alike.

This book highlights the experimental investigations that have been carried out on magnetic resonance imaging and computed tomography (MRI & CT) images using state-of-the-art Computational Image processing techniques, and tabulates the statistical values wherever necessary. In a very simple and straightforward way, it explains how image processing methods are used to improve the quality of medical images and facilitate analysis. It offers a valuable resource for researchers, engineers, medical doctors and bioinformatics experts alike.

This book is a collection of all the experimental results and analysis carried out on medical images of diabetic related causes. The experimental investigations have been carried out on images starting from very basic image processing techniques such as image enhancement to sophisticated image segmentation methods. This book is intended to create an awareness on diabetes and its related causes and image processing methods used to detect and forecast in a very simple way. This book is useful to researchers, Engineers, Medical Doctors and Bioinformatics researchers.