9 Best New Feature Extraction Books To Read In 2020
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Unsupervised Feature Extraction Applied to Bioinformatics by Y-h. Taguchi made it to BookAuthority's best new Feature Extraction books!
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This book proposes applications of tensor decomposition to unsupervised feature extraction and feature selection. The author posits that although supervised methods including deep learning have become popular, unsupervised methods have their own advantages. He argues that this is the case because unsupervised methods are easy to learn since tensor decomposition is a conventional linear methodology. This book starts from very basic linear algebra and reaches the cutting edge methodologies applied to difficult situations when there are many features (variables) while only small number of samples are available.
...moreThe author includes advanced descriptions about tensor decomposition including Tucker decomposition using high order singular value decomposition as well as higher order orthogonal iteration, and train tenor decomposition. The author concludes by showing unsupervised methods and their application to a wide range of topicsAllows readers to analyze data sets with small samples and many features;Provides a fast algorithm, based upon linear algebra, to analyze big data;Includes several applications to multi-view data analyses, with a focus on bioinformatics
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This book presents the conceptual and mathematical basis and the implementation of both electroencephalogram (EEG) and EEG signal processing in a comprehensive, simple, and easy-to-understand manner. EEG records the electrical activity generated by the firing of neurons within human brain at the scalp. They are widely used in clinical neuroscience, psychology, and neural engineering, and a series of EEG signal-processing techniques have been developed.
...moreIntended for cognitive neuroscientists, psychologists and other interested readers, the book discusses a range of current mainstream EEG signal-processing and feature-extraction techniques in depth, and includes chapters on the principles and implementation strategies
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This book describes the latest advances in pulse signal analysis and their applications in classification and diagnosis. First, it provides a comprehensive introduction to useful techniques for pulse signal acquisition based on different kinds of pulse sensors together with the optimized acquisition scheme. It then presents a number of preprocessing and feature extraction methods, as well as case studies of the classification methods used. Lastly it discusses some promising directions for the future study and clinical applications of pulse signal analysis.
...moreThe book is a valuable resource for researchers, professionals and postgraduate students working in the field of pulse diagnosis, signal processing, pattern recognition and biometrics. It is also useful for those involved in interdisciplinary research
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This book is applicable for the study in Computer Science and Engineering students for UG level and PG level of all Indian Universities. Book contains Fingerprint Image Enhancement, Fingerprint Classification Techniques and Basic concept of Fingerprint Feature Extraction. The book presents a biometric, an automated way of recognizing an individual based on a physiological or behavioral characteristic. Fingerprints are most widely used biometric feature for identification and authentication.
...moreThe book determines that there are several efficient methods for fingerprint recognition has ever remained a source of great attraction to many workers due to their wide application in various fields. The book describes the concept of the fingerprint feature extraction, it has been observed that most of the existing work is aimed to feature extraction the fingerprint database based on the minutiae sets, singular points and other techniques.
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We picked a method, now what? What methods are feasible and acceptable to estimate the impact of reforms? Is Feature extraction dependent on the successful delivery of a current project? How will we ensure we get what we expected? Can the solution be designed and implemented within an acceptable time period?
Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department
Unless you are talking a one-time, single-use project, there should be a process.
...moreDefining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department
Unless you are talking a one-time, single-use project, there should be a process.
Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Feature extraction investments work better This Feature extraction All-Inclusive Self-Assessment enables You to be that person All the tools you need to an in-depth Feature extraction Self-Assessment. Featuring 676 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Feature extraction improvements can be made In using the questions you will be better able to: - diagnose Feature extraction projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Feature extraction and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Feature extraction Scorecard, you will develop a clear picture of which Feature extraction areas need attention Your purchase includes access details to the Feature extraction self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in.. - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Feature extraction Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips
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EEG-Based Diagnosis of Alzheimer Disease: A Review and Novel Approaches for Feature Extraction and Classification Techniques provides a practical and easy-to-use guide for researchers in EEG signal processing techniques, Alzheimer’s disease, and dementia diagnostics. The book examines different features of EEG signals used to properly diagnose Alzheimer’s Disease early, presenting new and innovative results in the extraction and classification of Alzheimer’s Disease using EEG signals.
...moreThis book brings together the use of different EEG features, such as linear and nonlinear features, which play a significant role in diagnosing Alzheimer’s DiseaseIncludes the mathematical models and rigorous analysis of various classifiers and machine learning algorithms from a perspective of clinical deploymentCovers the history of EEG signals and their measurement and recording, along with their uses in clinical diagnosticsAnalyzes spectral, wavelet, complexity and other features of early and efficient Alzheimer’s Disease diagnosticsExplores support vector machine-based classification to increase accuracy
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This book presents state-of-the-art methodologies and a comprehensive introduction to the recognition and representation of species and individual animals based on their physiological and phenotypic appearances, biometric characteristics, and morphological image patterns. It provides in-depth coverage of this emerging area, with an emphasis on the design and analysis techniques used in visual animal biometrics-based recognition systems
...moreThe book offers a comprehensive introduction to visual animal biometrics, addressing a range of recent advances and practices like sensing, feature extraction, feature selection and representation, matching, indexing of feature sets, and animal biometrics-based multimodal systems. It provides authoritative information on all the major concepts, as well as highly specific topics, e.g. the identification of cattle based on their muzzle point image pattern and face images to prevent false insurance claims, or the monitoring and registration of animals based on their biometric features As such, the book provides a sound platform for understanding the Visual Animal Biometrics paradigm, a vital catalyst for researchers in the field, and a valuable guide for professionals. In addition, it can help both private and public organizations adapt and enhance their classical animal recognition systems.
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Computer-Aided Detection (CAD) of breast cancer helps the radiologists in early diagnosis of breast cancer with good accuracy in a very cost-effective way. There is a growing interest for breast ultrasound (BUS) diagnosis owing to its efficiency and portability. However, the presence of speckle noise, low contrast and blurred boundary of mass in a BUS image make it challenging to determine the mass. In the current work, a CAD system is proposed for the diagnosis of breast cancer from BUS images. The methodology includes the phases of preprocessing, segmentation, feature extraction and classification of BUS images.
...moreThe preprocessing algorithm used in this work efficiently removes noise and enhances the contrast of BUS images. Segmenting an accurate region of interest in turn results in efficient feature extraction and classification of BUS images into benign and malignant ones. The proposed CAD system has been tested on Matlab platform with several images to obtain reasonably good accuracy, specificity, and sensitivity. Moreover, hardware/software co-simulation of preprocessing and active contour based segmentation algorithm on Xilinx Zynq has been performed using Vivado HLS.
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A good text recognizer has many commercial and practical applications, e.g. from searching data in scanned book to automation of any organization, like post office, which involve manual task of interpreting text. The problem of text recognition has been attempted by many different approaches. In Feature extraction approach, statistical distribution of points is analyzed and orthogonal properties extracted. For each symbol a feature vector is calculated and stored in database.
...moreAnd recognition is done by finding distance of feature vector of input image to that of stored in the database, and outputting the symbol with minimum deviation. Though this technique gives lot better results on handwritten characters, but is very sensitive to noise and edge thickness. Template matching is one of the simplest approaches. In this many templates of each word are maintained for a input image, error or difference with each template is computed. The symbol corresponding to minimum error is output.
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