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Hybrid Metaheuristics: Research And Applications
A metaheuristic is a higher-level procedure designed to select a partial search algorithm that may lead to a good solution to an optimization problem, especially with incomplete or imperfect information.This unique compendium focuses on the insights of hybrid metaheuristics. It illustrates the recent researches on evolving novel hybrid metaheuristic algorithms, and prominently highlights its diverse application areas. As such, the book helps readers to grasp the essentials of hybrid metaheuristics and to address real world problems.The must-have volume serves as an inspiring read for professionals, researchers, academics and graduate students in the fields of artificial intelligence, robotics and machine learning.Related Link(s)
Biomedical Signal and Image Processing with Artificial Intelligence
This book focuses on advanced techniques used for feature extraction, analysis, recognition, and classification in the area of biomedical signal and image processing. Contributions cover all aspects of artificial intelligence, machine learning, and deep learning in the field of biomedical signal and image processing using novel and unexplored techniques and methodologies. The book covers recent developments in both medical images and signals analyzed by artificial intelligence techniques. The authors also cover topics related to development based artificial intelligence, which includes machine learning, neural networks, and deep learning. This book will provide a platform for researchers who are working in the area of artificial intelligence for biomedical applications. Provides insights into medical signal and image analysis using artificial intelligence; Includes novel and recent trends of decision support system for medical research; Outlines employment of evolutionary algorithms for biomedical data, big data analysis for medical databases, and reliability, opportunities, and challenges in clinical data.
IoT Applications for Healthcare Systems
This book discusses communications technologies used in the field of healthcare, including IoT, soft computing, machine learning, big data, augmented reality, and wearable sensors. The book presents various applications that are helpful for research scholars and scientists who are working toward identifying and pinpointing the potential of this technology. The book also helps researchers and practitioners to understand and analyze the e-healthcare architecture through IoT and the state-of-the-art in IoT countermeasures with real-time challenges. Topics of interest include healthcare systems based on advanced development boards, mobile health parameters recording and monitoring systems, remote health / patient monitoring, hospital operations management, abnormality / disease detection by IoT devices, and efficient drug management. The book is relevant to a range of researchers, academics, and practitioners working on the intersection of IoT and healthcare.
Recent Trends in Blockchain for Information Systems Security and Privacy
Blockchain technology is an emerging distributed, decentralized architecture and computing paradigm, which has accelerated the development and application of cloud, fog and edge computing; artificial intelligence; cyber physical systems; social networking; crowdsourcing and crowdsensing; 5g; trust management and finance; and other many useful sectors. Nowadays, the primary blockchain technology uses are in information systems to keep information secure and private. However, many threats and vulnerabilities are facing blockchain in the past decade such 51% attacks, double spending attacks, etc. The popularity and rapid development of blockchain brings many technical and regulatory challenges ...
Encyclopedia of Image Processing
The Encyclopedia of Image Processing presents a vast collection of well-written articles covering image processing fundamentals (e.g. color theory, fuzzy sets, cryptography) and applications (e.g. geographic information systems, traffic analysis, forgery detection). Image processing advances have enabled many applications in healthcare, avionics, robotics, natural resource discovery, and defense, which makes this text a key asset for both academic and industrial libraries and applied scientists and engineers working in any field that utilizes image processing. Written by experts from both academia and industry, it is structured using the ACM Computing Classification System (CCS) first published in 1988, but most recently updated in 2012.
Proceedings of the 2009 International Conference on Signals, Systems and Automation (ICSSA 2009)
This book is a collection of papers from the 2009 International Conference on Signals, Systems and Automation (ICSSA 2009). The conference at a glance: - Pre-conference Workshops/Tutorials on 27th Dec, 2009 - Five Plenary talks - Paper/Poster Presentation: 28-29 Dec, 2009 - Demonstrations by SKYVIEWInc, SLS Inc., BSNL, Baroda Electric Meters, SIS - On line paper submission facility on website - 200+ papers are received from India and abroad - Delegates from different countries including Poland, Iran, USA - Delegates from 16 states of India - Conference website is seen by more than 3000 persons across the world (27 countries and 120 cities)
Proceedings of the Multi-Conference 2011
The International Conference on Signals, Systems and Automation (ICSSA 2011) aims to spread awareness in the research and academic community regarding cutting-edge technological advancements revolutionizing the world. The main emphasis of this conference is on dissemination of information, experience, and research results on the current topics of interest through in-depth discussions and participation of researchers from all over the world. The objective is to provide a platform to scientists, research scholars, and industrialists for interacting and exchanging ideas in a number of research areas. This will facilitate communication among researchers in different fields of Electronics and Com...
2019 IEEE International Conference on Signal Processing, Information, Communication and Systems (SPICSCON)
Audio and acoustic signal processing Speech and language processing Image and video processing Multimedia communication and signal processing Signal processing for internet of things Sensor array and multichannel signal processing Signal processing for communications Radar and sonar signal processing 3G 4G 5G Mobile Communication and Network Communication Device Modeling Network,Information and Cyber Security Microwave MM Wave THz Circuits and System Wireless and Wearable Technology Signal processing for Graphs and Networks Computer Vision, Graphic and Virtual Reality Cloud and ICT Wireless and Optical Communication Biomedical Circuits & Systems Power and Energy Circuits & Systems Digital Circuits & Systems Sensory Circuits & Systems Nonlinear and adaptive signal processing Compressed sensing and sparse modelling Pattern Recognition & Artificial Intelligence Machine learning & Deep Learning Biomedical Signal and Image Processing
Wireless Communication
Beginning with an overview of current scenario in the study of wireless communication systems and the presentation of fundamental concepts, the book gradually discusses each block of wireless link in detail including coding, modulation and the advanced topics such as multiplexing, mobile communication, software radio, OFDM and MIMO. All the chapters start with the simpler topics and gradually build up the advanced concepts through detailed explanations and illustrations. The chapters are extremely student friendly with rich pedagogy including case studies, solved examples, review questions, numerical problems and multiple choice questions to help students revise the concepts learnt through visualization and practice.
Deep Learning in Healthcare
This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems. Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data. Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.
