Computational Intelligence for Signal and Image Processing
Author: Baiyuan Ding
Publisher: Frontiers Media SA
Published: 2023-10-17
Total Pages: 134
ISBN-13: 2832535461
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Signal and Image Processing Techniques for the Development of Intelligent Healthcare Systems
Author: E. Priya
Publisher: Springer Nature
Published: 2020-09-21
Total Pages: 290
ISBN-13: 9811561419
DOWNLOAD EBOOKThis book comprehensively reviews the various automated and semi-automated signal and image processing techniques, as well as deep-learning-based image analysis techniques, used in healthcare diagnostics. It highlights a range of data pre-processing methods used in signal processing for effective data mining in remote healthcare, and discusses pre-processing using filter techniques, noise removal, and contrast-enhanced methods for improving image quality. The book discusses the status quo of artificial intelligence in medical applications, as well as its future. Further, it offers a glimpse of feature extraction methods for reducing dimensionality and extracting discriminatory information hidden in biomedical signals. Given its scope, the book is intended for academics, researchers and practitioners interested in the latest real-world technological innovations.
Image and Signal Processing
Author: Alamin Mansouri
Publisher: Springer
Published: 2018-06-29
Total Pages: 551
ISBN-13: 3319942115
DOWNLOAD EBOOKThis book constitutes the refereed proceedings of the 8th International Conference on Image and Signal Processing, ICISP 2018, held in Cherbourg, France, in July 2018. The 58 revised full papers were carefully reviewed and selected from 122 submissions. The contributions report on the latest developments in image and signal processing, video processing, computer vision, multimedia and computer graphics, and mathematical imaging and vision.
Intelligent Image Processing
Author: Steve Mann
Publisher: Wiley-IEEE Press
Published: 2002
Total Pages: 368
ISBN-13:
DOWNLOAD EBOOKIntelligent Image Processing describes the EyeTap technology that allows non-invasive tapping into the human eye through devices built into eyeglass frames. This isn't merely about a computer screen inside eyeglasses, but rather the ability to have a shared telepathic experience among viewers. Written by the developer of the EyeTap principle, this work explores the practical application and far-reaching implications this new technology has for human telecommunications.
Biomedical Signal Processing and Artificial Intelligence in Healthcare
Author: Walid A. Zgallai
Publisher: Academic Press
Published: 2020-07-29
Total Pages: 270
ISBN-13: 0128189479
DOWNLOAD EBOOKBiomedical Signal Processing and Artificial Intelligence in Healthcare is a new volume in the Developments in Biomedical Engineering and Bioelectronics series. This volume covers the basics of biomedical signal processing and artificial intelligence. It explains the role of machine learning in relation to processing biomedical signals and the applications in medicine and healthcare. The book provides background to statistical analysis in biomedical systems. Several types of biomedical signals are introduced and analyzed, including ECG and EEG signals. The role of Deep Learning, Neural Networks, and the implications of the expansion of artificial intelligence is covered. Biomedical Images are also introduced and processed, including segmentation, classification, and detection. This book covers different aspects of signals, from the use of hardware and software, and making use of artificial intelligence in problem solving.Dr Zgallai's book has up to date coverage where readers can find the latest information, easily explained, with clear examples and illustrations. The book includes examples on the application of signal and image processing employing artificial intelligence to Alzheimer, Parkinson, ADHD, autism, and sleep disorders, as well as ECG and EEG signals. Developments in Biomedical Engineering and Bioelectronics is a 10-volume series which covers recent developments, trends and advances in this field. Edited by leading academics in the field, and taking a multidisciplinary approach, this series is a forum for cutting-edge, contemporary review articles and contributions from key 'up-and-coming' academics across the full subject area. The series serves a wide audience of university faculty, researchers and students, as well as industry practitioners. - Coverage of the subject area and the latest advances and applications in biomedical signal processing and Artificial Intelligence - Contributions by recognized researchers and field leaders - On-line presentations, tutorials, application and algorithm examples
Speech, Audio, Image and Biomedical Signal Processing using Neural Networks
Author: Bhanu Prasad
Publisher: Springer Science & Business Media
Published: 2008-01-03
Total Pages: 419
ISBN-13: 3540753974
DOWNLOAD EBOOKHumans are remarkable in processing speech, audio, image and some biomedical signals. Artificial neural networks are proved to be successful in performing several cognitive, industrial and scientific tasks. This peer reviewed book presents some recent advances and surveys on the applications of artificial neural networks in the areas of speech, audio, image and biomedical signal processing. It chapters are prepared by some reputed researchers and practitioners around the globe.
Applied Signal and Image Processing
Author: Rami Qahwaji
Publisher: IGI Global
Published: 2011
Total Pages: 0
ISBN-13: 9781609604776
DOWNLOAD EBOOKImage and signal processing techniques are receiving increasing interest because of their numerous real-world applications. Data is now available in different forms, different wavelengths, and even in different dimensions, creating the need for novel multidisciplinary solutions for automated data processing and analysis. Applied Signal and Image Processing: Multidisciplinary Advancements highlights the growing multidisciplinary nature of signal and image processing by focusing on emerging applications and recent advances in well-established fields. This book covers state-or-the-art applications in both signal and image processing, which include optical communication and sensing, wireless communication management, face recognition and facial imaging, solar imaging and feature detection, fractal analysis, and video processing.
Machine Intelligence and Signal Analysis
Author: M. Tanveer
Publisher: Springer
Published: 2018-08-07
Total Pages: 757
ISBN-13: 981130923X
DOWNLOAD EBOOKThe book covers the most recent developments in machine learning, signal analysis, and their applications. It covers the topics of machine intelligence such as: deep learning, soft computing approaches, support vector machines (SVMs), least square SVMs (LSSVMs) and their variants; and covers the topics of signal analysis such as: biomedical signals including electroencephalogram (EEG), magnetoencephalography (MEG), electrocardiogram (ECG) and electromyogram (EMG) as well as other signals such as speech signals, communication signals, vibration signals, image, and video. Further, it analyzes normal and abnormal categories of real-world signals, for example normal and epileptic EEG signals using numerous classification techniques. The book is envisioned for researchers and graduate students in Computer Science and Engineering, Electrical Engineering, Applied Mathematics, and Biomedical Signal Processing.
Machine Learning for Signal Processing
Author: Max A. Little
Publisher: Oxford University Press, USA
Published: 2019
Total Pages: 378
ISBN-13: 0198714939
DOWNLOAD EBOOKDescribes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Builds up concepts gradually so that the ideas and algorithms can be implemented in practical software applications.
Biosignal Processing and Classification Using Computational Learning and Intelligence
Author: Alejandro A. Torres-García
Publisher: Academic Press
Published: 2021-09-18
Total Pages: 538
ISBN-13: 0128204281
DOWNLOAD EBOOKBiosignal Processing and Classification Using Computational Learning and Intelligence: Principles, Algorithms and Applications posits an approach for biosignal processing and classification using computational learning and intelligence, highlighting that the term biosignal refers to all kinds of signals that can be continuously measured and monitored in living beings. The book is composed of five relevant parts. Part One is an introduction to biosignals and Part Two describes the relevant techniques for biosignal processing, feature extraction and feature selection/dimensionality reduction. Part Three presents the fundamentals of computational learning (machine learning). Then, the main techniques of computational intelligence are described in Part Four. The authors focus primarily on the explanation of the most used methods in the last part of this book, which is the most extensive portion of the book. This part consists of a recapitulation of the newest applications and reviews in which these techniques have been successfully applied to the biosignals' domain, including EEG-based Brain-Computer Interfaces (BCI) focused on P300 and Imagined Speech, emotion recognition from voice and video, leukemia recognition, infant cry recognition, EEGbased ADHD identification among others. - Provides coverage of the fundamentals of signal processing, including sensing the heart, sending the brain, sensing human acoustic, and sensing other organs - Includes coverage biosignal pre-processing techniques such as filtering, artifiact removal, and feature extraction techniques such as Fourier transform, wavelet transform, and MFCC - Covers the latest techniques in machine learning and computational intelligence, including Supervised Learning, common classifiers, feature selection, dimensionality reduction, fuzzy logic, neural networks, Deep Learning, bio-inspired algorithms, and Hybrid Systems - Written by engineers to help engineers, computer scientists, researchers, and clinicians understand the technology and applications of computational learning to biosignal processing
