Intelligent Algorithms In Ambient And Biomedical Computing
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Intelligent Algorithms In Ambient And Biomedical Computing
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Author : Wim Verhaegh
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-09-09
Intelligent Algorithms In Ambient And Biomedical Computing written by Wim Verhaegh and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-09 with Computers categories.
This book is the outcome of a series of discussions at the Philips Symposium on Intelligent Algorithms, held in Eindhoven in December 2004. It offers exciting and practical examples of the use of intelligent algorithms in ambient and biomedical computing. It contains topics such as bioscience computing, database design, machine consciousness, scheduling, video summarization, audio classification, semantic reasoning, machine learning, tracking and localization, secure computing, and communication.
Algorithms In Ambient Intelligence
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Author : W. Verhaegh
language : en
Publisher: Springer Science & Business Media
Release Date : 2004
Algorithms In Ambient Intelligence written by W. Verhaegh and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.
This book is the outcome of a series of discussions at the Philips Symposium on Intelligent Algorithms, which was held in Eindhoven on December 2002. It contains many exciting and practical examples from this newly developing research field, which can be positioned at the intersection of computer science, discrete mathematics, and artificial intelligence. The examples include machine learning, content management, vision, speech, content augmentation, profiling, music retrieval, feature extraction, audio and video fingerprinting, resource management, multimedia servers, network scheduling, and IC design.
Smart Health
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Author : Andreas Holzinger
language : en
Publisher: Springer
Release Date : 2015-02-24
Smart Health written by Andreas Holzinger and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-24 with Medical categories.
Prolonged life expectancy along with the increasing complexity of medicine and health services raises health costs worldwide dramatically. Whilst the smart health concept has much potential to support the concept of the emerging P4-medicine (preventive, participatory, predictive, and personalized), such high-tech medicine produces large amounts of high-dimensional, weakly-structured data sets and massive amounts of unstructured information. All these technological approaches along with “big data” are turning the medical sciences into a data-intensive science. To keep pace with the growing amounts of complex data, smart hospital approaches are a commandment of the future, necessitating context aware computing along with advanced interaction paradigms in new physical-digital ecosystems. The very successful synergistic combination of methodologies and approaches from Human-Computer Interaction (HCI) and Knowledge Discovery and Data Mining (KDD) offers ideal conditions for the vision to support human intelligence with machine learning. The papers selected for this volume focus on hot topics in smart health; they discuss open problems and future challenges in order to provide a research agenda to stimulate further research and progress.
Intelligent Computing Theories And Methodologies
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Author : De-Shuang Huang
language : en
Publisher: Springer
Release Date : 2015-08-10
Intelligent Computing Theories And Methodologies written by De-Shuang Huang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-10 with Computers categories.
This two-volume set LNCS 9225 and LNCS 9226 constitutes - in conjunction with the volume LNAI 9227 - the refereed proceedings of the 11th International Conference on Intelligent Computing, ICIC 2015, held in Fuzhou, China, in August 2015. The total of 191 full and 42 short papers presented in the three ICIC 2015 volumes was carefully reviewed and selected from 671 submissions. The papers are organized in topical sections such as evolutionary computation and learning; compressed sensing, sparse coding and social computing; neural networks, nature inspired computing and optimization; pattern recognition and signal processing; image processing; biomedical informatics theory and methods; differential evolution, particle swarm optimization and niche technology; intelligent computing and knowledge discovery and data mining; soft computing and machine learning; computational biology, protein structure and function prediction; genetic algorithms; artificial bee colony algorithms; swarm intelligence and optimization; social computing; information security; virtual reality and human-computer interaction; healthcare informatics theory and methods; unsupervised learning; collective intelligence; intelligent computing in robotics; intelligent computing in communication networks; intelligent control and automation; intelligent data analysis and prediction; gene expression array analysis; gene regulation modeling and analysis; protein-protein interaction prediction; biology inspired computing and optimization; analysis and visualization of large biological data sets; motif detection; biomarker discovery; modeling; simulation; and optimization of biological systems; biomedical data modeling and mining; intelligent computing in biomedical signal/image analysis; intelligent computing in brain imaging; neuroinformatics; cheminformatics; intelligent computing in computational biology; computational genomics; special session on biomedical data integration and mining in the era of big data; special session on big data analytics; special session on artificial intelligence for ambient assisted living; and special session on swarm intelligence with discrete dynamics.
Intelligent Computing Theories And Methodologies
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Author : De-Shuang Huang
language : en
Publisher: Springer
Release Date : 2015-08-10
Intelligent Computing Theories And Methodologies written by De-Shuang Huang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-10 with Computers categories.
This two-volume set LNCS 9225 and LNCS 9226 constitutes - in conjunction with the volume LNAI 9227 - the refereed proceedings of the 11th International Conference on Intelligent Computing, ICIC 2015, held in Fuzhou, China, in August 2015. The total of 191 full and 42 short papers presented in the three ICIC 2015 volumes was carefully reviewed and selected from 671 submissions. The papers are organized in topical sections such as evolutionary computation and learning; compressed sensing, sparse coding and social computing; neural networks, nature inspired computing and optimization; pattern recognition and signal processing; image processing; biomedical informatics theory and methods; differential evolution, particle swarm optimization and niche technology; intelligent computing and knowledge discovery and data mining; soft computing and machine learning; computational biology, protein structure and function prediction; genetic algorithms; artificial bee colony algorithms; swarm intelligence and optimization; social computing; information security; virtual reality and human-computer interaction; healthcare informatics theory and methods; unsupervised learning; collective intelligence; intelligent computing in robotics; intelligent computing in communication networks; intelligent control and automation; intelligent data analysis and prediction; gene expression array analysis; gene regulation modeling and analysis; protein-protein interaction prediction; biology inspired computing and optimization; analysis and visualization of large biological data sets; motif detection; biomarker discovery; modeling; simulation; and optimization of biological systems; biomedical data modeling and mining; intelligent computing in biomedical signal/image analysis; intelligent computing in brain imaging; neuroinformatics; cheminformatics; intelligent computing in computational biology; computational genomics; special session on biomedical data integration and mining in the era of big data; special session on big data analytics; special session on artificial intelligence for ambient assisted living; and special session on swarm intelligence with discrete dynamics.
Bio Inspired Systems Computational And Ambient Intelligence
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Author : Joan Cabestany
language : en
Publisher: Springer
Release Date : 2009-06-05
Bio Inspired Systems Computational And Ambient Intelligence written by Joan Cabestany and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-05 with Computers categories.
This volume presents the set of final accepted papers for the tenth edition of the IWANN conference “International Work-Conference on Artificial neural Networks” held in Salamanca (Spain) during June 10–12, 2009. IWANN is a biennial conference focusing on the foundations, theory, models and applications of systems inspired by nature (mainly, neural networks, evolutionary and soft-computing systems). Since the first edition in Granada (LNCS 540, 1991), the conference has evolved and matured. The list of topics in the successive Call for - pers has also evolved, resulting in the following list for the present edition: 1. Mathematical and theoretical methods in computational intelligence. C- plex and social systems. Evolutionary and genetic algorithms. Fuzzy logic. Mathematics for neural networks. RBF structures. Self-organizing networks and methods. Support vector machines. 2. Neurocomputational formulations. Single-neuron modelling. Perceptual m- elling. System-level neural modelling. Spiking neurons. Models of biological learning. 3. Learning and adaptation. Adaptive systems. Imitation learning. Reconfig- able systems. Supervised, non-supervised, reinforcement and statistical al- rithms. 4. Emulation of cognitive functions. Decision making. Multi-agent systems. S- sor mesh. Natural language. Pattern recognition. Perceptual and motor functions (visual, auditory, tactile, virtual reality, etc.). Robotics. Planning motor control. 5. Bio-inspired systems and neuro-engineering. Embedded intelligent systems. Evolvable computing. Evolving hardware. Microelectronics for neural, fuzzy and bio-inspired systems. Neural prostheses. Retinomorphic systems. Bra- computer interfaces (BCI). Nanosystems. Nanocognitive systems.
Trends In Deep Learning Methodologies
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Author : Vincenzo Piuri
language : en
Publisher: Academic Press
Release Date : 2020-11-12
Trends In Deep Learning Methodologies written by Vincenzo Piuri and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-12 with Computers categories.
Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters elaborate on these models which have shown significant success in dealing with massive data for a large number of applications, given their capacity to extract complex hidden features and learn efficient representation in unsupervised settings. Chapters investigate deep learning-based algorithms in a variety of application, including biomedical and health informatics, computer vision, image processing, and more. In recent years, many powerful algorithms have been developed for matching patterns in data and making predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. Deep learning methods can deal with multiple levels of representation in which the system learns to abstract higher level representations of raw data. Earlier, it was a common requirement to have a domain expert to develop a specific model for each specific application, however, recent advancements in representation learning algorithms allow researchers across various subject domains to automatically learn the patterns and representation of the given data for the development of specific models. Provides insights into the theory, algorithms, implementation and the application of deep learning techniques Covers a wide range of applications of deep learning across smart healthcare and smart engineering Investigates the development of new models and how they can be exploited to find appropriate solutions
Distributed Computing Artificial Intelligence Bioinformatics Soft Computing And Ambient Assisted Living
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Author : Sigeru Omatu
language : en
Publisher: Springer
Release Date : 2009-06-06
Distributed Computing Artificial Intelligence Bioinformatics Soft Computing And Ambient Assisted Living written by Sigeru Omatu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-06 with Computers categories.
This volume (II) contains all publications accepted for the symposiums and workshops held in parallel with the 10th International Work-Conference on Artificial Neural Networks (IWANN 2009), covering a wide spectrum of technological areas such as distributed computing, artificial intelligence, bioinformatics, soft computing and ambient-assisted living: • DCAI 2009 (International Symposium on Distributed Computing and Artificial Intelligence), covering artificial intelligence and its applications in distributed environments, such as the Internet, electronic commerce, mobile communi- tions, wireless devices, distributed computing, and so on. This event accepted a total of 96 submissions selected from a submission pool of 157 papers, from 12 different countries. • IWAAL 2009 (International Workshop of Ambient-Assisted Living), covering solutions aimed at increasing the quality of life, safety and health problems of elderly and disabled people by means of technology. This event accepted a - tal of 42 submissions selected from a submission pool of 78 papers, from 9 d- ferent countries. • IWPACBB 2009 (Third International Workshop on Practical Applications of Computational Biology and Bioinformatics), covering computational biology and bioinformatics as a possibility for knowledge discovery, modelling and - timization tasks, aiming at the development of computational models so that the response of biological complex systems to any perturbation can be p- dicted. This event accepted a total of 39 submissions selected from a subm- sion pool of 75 papers, from 6 different countries.
Computational Intelligence And Biomedical Signal Processing
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Author : Mitul Kumar Ahirwal
language : en
Publisher: Springer Nature
Release Date : 2021-05-25
Computational Intelligence And Biomedical Signal Processing written by Mitul Kumar Ahirwal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-25 with Technology & Engineering categories.
This book presents an interdisciplinary paradigms of computational intelligence techniques and biomedical signal processing. The computational intelligence techniques outlined in the book will help to develop various ways to enhance and utilize signal processing algorithms in the field of biomedical signal processing. In this book, authors have discussed research, discoveries and innovations in computational intelligence, signal processing, and biomedical engineering that will be beneficial to engineers working in the field of health care systems. The book provides fundamental and initial level theory and implementation tools, so that readers can quickly start their research in these interdisciplinary domains.
Machine Learning In Bio Signal Analysis And Diagnostic Imaging
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Author : Nilanjan Dey
language : en
Publisher: Academic Press
Release Date : 2018-11-30
Machine Learning In Bio Signal Analysis And Diagnostic Imaging written by Nilanjan Dey and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-30 with Science categories.
Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as PCA, SVM, techniques, Naive Bayes, Neural Network, Decision trees, and Association Rule Mining are among the approaches presented. The design of high accuracy decision support systems assists and eases the job of healthcare practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the demands of radiologists in improving the efficiency and quality of diagnosis in dealing with unique and complex diseases in real time by reducing human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and medical schools, researchers and engineers. Examines a variety of machine learning techniques applied to bio-signal analysis and diagnostic imaging Discusses various methods of using intelligent systems based on machine learning, soft computing, computer vision, artificial intelligence and data mining Covers the most recent research on machine learning in imaging analysis and includes applications to a number of domains