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The proceedings includes cutting-edge research articles from the Fourth International Conference on Signal and Image Processing (ICSIP), which is organised by Dr. N.G.P. Institute of Technology, Kalapatti, Coimbatore. The Conference provides academia and industry to discuss and present the latest technological advances and research results in the fields of theoretical, experimental, and application of signal, image and video processing. The book provides latest and most informative content from engineers and scientists in signal, image and video processing from around the world, which will benefit the future research community to work in a more cohesive and collaborative way.
The book is a collection of best selected research papers presented at the Fourth International Conference on Communication, Devices and Computing (ICCDC 2023). The book covers new ideas, applications and experiences of research engineers, scientists, industrialists, scholars and students from in and around the globe. It covers research contributions from communication technologies which are from the areas such as 5G communication, next-generation Wi-Fi, spread spectrum systems, satellite and high altitude platforms, radio over fiber techniques, wireless sensor networks, modulation and diversity technique, ad hoc and mesh networks, cognitive radio networking, optical wireless and visible light communications, signal processing for secure communication, millimeter wave and terahertz communication, design, control and management of optical network, error control coding and information theory, printed antennas, performance analysis of wireless network, smart antennas and space time processing.
This edited volume contains a selection of refereed and revised papers originally presented at the International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS-2014), March 13-15, 2014, Trivandrum, India. The program committee received 134 submissions from 11 countries. Each paper was peer reviewed by at least three or more independent referees of the program committee and the 52 papers were finally selected. The papers offer stimulating insights into Pattern Recognition, Machine Learning and Knowledge-Based Systems; Signal and Speech Processing; Image and Video Processing; Mobile Computing and Applications and Computer Vision. The book is directed to the researchers and scientists engaged in various field of signal processing and related areas.
This book presents state-of-the-art optimization algorithms followed by Internet of Things (IoT) fundamentals. The applications of machine learning and IoT are explored, with topics including optimization, algorithms and machine learning in image processing and IoT. Applications of Optimization and Machine Learning in Image Processing and IoT is a complete reference source, providing the latest research findings and solutions for optimization and machine learning algorithms. The chapters examine and discuss the fields of machine learning, IoT and image processing. KEY FEATURES: • Includes fundamental concepts towards advanced applications in machine learning and IoT. • Discusses potential and challenges of machine learning for IoT and optimization • Reviews recent advancements in diverse researches on computer vision, networking and optimization field. • Presents latest technologies such as machine learning in image processing and IoT This book has been written for readers in academia, engineering, IT specialists, researchers, industrial professionals and students, and is a great reference for those just starting out in the field as well as those at an advanced level.
As more and more of our data is stored remotely, accessing that data wherever and whenever it is needed is a critical concern. More concerning is managing the databanks and storage space necessary to enable cloud systems. Resource Management of Mobile Cloud Computing Networks and Environments reports on the latest advances in the development of computationally intensive and cloud-based applications. Covering a wide range of problems, solutions, and perspectives, this book is a scholarly resource for specialists and end-users alike making use of the latest cloud technologies.
This book presents non-linear image enhancement approaches to mammograms as a robust computer-aided analysis solution for the early detection of breast cancer, and provides a compendium of non-linear mammogram enhancement approaches: from the fundamentals to research challenges, practical implementations, validation, and advances in applications. The book includes a comprehensive discussion on breast cancer, mammography, breast anomalies, and computer-aided analysis of mammograms. It also addresses fundamental concepts of mammogram enhancement and associated challenges, and features a detailed review of various state-of-the-art approaches to the enhancement of mammographic images and emerging research gaps. Given its scope, the book offers a valuable asset for radiologists and medical experts (oncologists), as mammogram visualization can enhance the precision of their diagnostic analyses; and for researchers and engineers, as the analysis of non-linear filters is one of the most challenging research domains in image processing.
This book addresses and disseminates research and development in the applications of intelligent techniques for computer vision, the field that works on enabling computers to see, identify, and process images in the same way that human vision does, and then providing appropriate output. The book provides contributions which include theory, case studies, and intelligent techniques pertaining to computer vision applications. The book helps readers grasp the essence of the recent advances in this complex field. The audience includes researchers, professionals, practitioners, and students from academia and industry who work in this interdisciplinary field. The authors aim to inspire future research both from theoretical and practical viewpoints to spur further advances in the field.
The proceedings includes cutting-edge research articles from the Fourth International Conference on Signal and Image Processing (ICSIP), which is organised by Dr. N.G.P. Institute of Technology, Kalapatti, Coimbatore. The Conference provides academia and industry to discuss and present the latest technological advances and research results in the fields of theoretical, experimental, and application of signal, image and video processing. The book provides latest and most informative content from engineers and scientists in signal, image and video processing from around the world, which will benefit the future research community to work in a more cohesive and collaborative way.
The proceedings includes cutting-edge research articles from the Fourth International Conference on Signal and Image Processing (ICSIP), which is organised by Dr. N.G.P. Institute of Technology, Kalapatti, Coimbatore. The Conference provides academia and industry to discuss and present the latest technological advances and research results in the fields of theoretical, experimental, and application of signal, image and video processing. The book provides latest and most informative content from engineers and scientists in signal, image and video processing from around the world, which will benefit the future research community to work in a more cohesive and collaborative way.
The Fourier transform is one of the most fundamental tools for computing the frequency representation of signals. It plays a central role in signal processing, communications, audio and video compression, medical imaging, genomics, astronomy, as well as many other areas. Because of its widespread use, fast algorithms for computing the Fourier transform can benefit a large number of applications. The fastest algorithm for computing the Fourier transform is the Fast Fourier Transform (FFT), which runs in near-linear time making it an indispensable tool for many applications. However, today, the runtime of the FFT algorithm is no longer fast enough especially for big data problems where each dataset can be few terabytes. Hence, faster algorithms that run in sublinear time, i.e., do not even sample all the data points, have become necessary. This book addresses the above problem by developing the Sparse Fourier Transform algorithms and building practical systems that use these algorithms to solve key problems in six different applications: wireless networks; mobile systems; computer graphics; medical imaging; biochemistry; and digital circuits. This is a revised version of the thesis that won the 2016 ACM Doctoral Dissertation Award.