Surekha Borra Reihenfolge der Bücher

Thanks to recent advances in sensors, communication and satellite technology, data storage, processing and networking capabilities, satellite image acquisition and mining are now on the rise. In turn, satellite images play a vital role in providing essential geographical information. Highly accurate automatic classification and decision support systems can facilitate the efforts of data analysts, reduce human error, and allow the rapid and rigorous analysis of land use and land cover information. Integrating Machine Learning (ML) technology with the human visual psychometric can help meet geologists’ demands for more efficient and higher-quality classification in real time. This book introduces readers to key concepts, methods and models for satellite image analysis; highlights state-of-the-art classification and clustering techniques; discusses recent developments and remaining challenges; and addresses various applications, making it a valuable asset for engineers, data analysts and researchers in the fields of geographic information systems and remote sensing engineering.

Intelligent prediction and decision support systems leverage signal processing, computer vision, machine learning, software engineering, knowledge-based systems, data mining, and artificial intelligence. These systems, rooted in expert systems, genetic algorithms, artificial neural networks, and fuzzy logic, offer significant benefits in design, manufacturing, healthcare, and commercial software development. Key advantages include cost savings through expert system technology, expedited decision-making, timely project completion, enhanced product development, improved decision-making quality, and the preservation of individual expertise. They simplify complex decision problems, exemplified by applications in healthcare diagnostics. This book addresses the challenges associated with the development, implementation, and application of these systems across various domains. It aims to compile a diverse array of high-quality articles, including original research, methodological reviews, survey papers, case studies, and reports. Topics will encompass intelligent systems, expert prediction systems, evaluation models, decision support systems, and computer-aided diagnosis, providing a comprehensive resource for understanding and advancing these technologies.

The Book presents an overview of newly developed watermarking techniques in various independent and hybrid domainsCovers the basics of digital watermarking, its types, domain in which it is implemented and the application of machine learning algorithms onto digital watermarkingReviews hardware implementation of watermarkingDiscusses optimization problems and solutions in watermarking with a special focus on bio-inspired algorithmsIncludes a case study along with its MATLAB code and simulation results