Advances in Pattern Recognition and Artificial Intelligence, Nicola Nobile, Marleah Blom, Ching Y Suen
Автор: Kristin J. Dana Название: Computational Texture and Patterns: From Textons to Deep Learning ISBN: 1681730111 ISBN-13(EAN): 9781681730110 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 51750.00 T Наличие на складе: Невозможна поставка. Описание: Visual pattern analysis is a fundamental tool in mining data for knowledge. Computational representations for patterns and texture allow us to summarize, store, compare, and label in order to learn about the physical world. Our ability to capture visual imagery with cameras and sensors has resulted in vast amounts of raw data, but using this information effectively in a task-specific manner requires sophisticated computational representations. We enumerate specific desirable traits for these representations: (1) intraclass invariance—to support recognition; (2) illumination and geometric invariance for robustness to imaging conditions; (3) support for prediction and synthesis to use the model to infer continuation of the pattern; (4) support for change detection to detect anomalies and perturbations; and (5) support for physics-based interpretation to infer system properties from appearance. In recent years, computer vision has undergone a metamorphosis with classic algorithms adapting to new trends in deep learning. This text provides a tour of algorithm evolution including pattern recognition, segmentation and synthesis. We consider the general relevance and prominence of visual pattern analysis and applications that rely on computational models.
Автор: Danel Jaso Название: Pattern Recognition Techniques, Technology & Applications ISBN: 1681174642 ISBN-13(EAN): 9781681174648 Издательство: Gazelle Book Services Рейтинг: Цена: 217350.00 T Наличие на складе: Невозможна поставка. Описание: This book highlights recent advances and new ideas in promoting the techniques, technology and applications of pattern recognition. The book provides a comprehensive overview of the developments of techniques and approaches on pattern recognition. Pattern recognition is the science of making inferences from perceptual data, using tools from statistics, probability, computational geometry, machine learning, signal processing, and algorithm design. A wealth of advanced pattern recognition algorithms are emerging from the interdiscipline between technologies of effective visual features and the human-brain cognition process. Effective visual features are made possible through the rapid developments in appropriate sensor equipments, novel filter designs, and viable information processing architectures. While the understanding of human-brain cognition process broadens the way in which the computer can perform pattern recognition task. Pattern recognition is the imposition of identity on input data, such as speech, images, or a stream of text, by the recognition and delineation of patterns it contains and their relationships. Stages in pattern recognition may involve measurement of the object to identify distinguishing attributes, extraction of features for the defining attributes, and comparison with known patterns to determine a match or mismatch. Pattern recognition has extensive application in astronomy, medicine, robotics, and remote sensing by satellites.
Автор: Bilroy Muller Название: Vision Systems: Segmentation & Pattern Recognition ISBN: 1681175894 ISBN-13(EAN): 9781681175898 Издательство: Gazelle Book Services Рейтинг: Цена: 230210.00 T Наличие на складе: Невозможна поставка. Описание: Computer vision is the most important key in developing autonomous navigation systems for interaction with the environment. It also leads us to marvel at the functioning of our own vision system. Research in computer vision has exponentially improved in the last two decades because of the convenience of cheap cameras and fast processors. This increase has also been accompanied by a blurring of the boundaries between the different applications of vision, making it truly interdisciplinary. Vision systems can be thought of as computers with eyes that can identify, inspect and communicate critical information to eliminate costly errors, improve productivity and enhance customer satisfaction through the consistent delivery of quality products. Primarily used for online inspection, vision systems can perform complex or mundane repetitive tasks at high speed with high accuracy and high consistency. Vision Systems: Segmentation and Pattern Recognition attempted to put together state-of-the-art research and developments in segmentation and pattern recognition.
Автор: Siddhartha Bhattacharyya, Vaclav Snasel, Aboul Ella Hassanien, Satadal Saha, B. K. Tripathy Название: Deep Learning: Research and Applications ISBN: 3110670798 ISBN-13(EAN): 9783110670790 Издательство: Walter de Gruyter Цена: 136310.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book will focus on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it would provide an insight of deep neural networks in action with illustrative coding examples. Moreover, the book will also provide video demonstrations on each chapter. Deep learning is a new area of machine learning research, which has been introduced with the objective of moving ML closer to one of its original goals, i.e. artificial intelligence. Deep learning was developed as an ML approach to deal with complex input-output mappings. While traditional methods successfully solve problems where final value is a simple function of input data, deep learning techniques are able to capture composite relations between non immediately related fields, for example between air pressure recordings and english words, millions of pixels and textual description, brand-related news and future stock prices and almost all real world problems. Deep learning is a class of nature inspired machine learning algorithms that uses a cascade of multiple layers of nonlinear processing units for feature extraction and transformation. Each successive layer uses the output from the previous layer as input. The learning may be supervised (e.g., classification) and/or unsupervised (e.g., pattern analysis) manners. These algorithms learn multiple levels of representations that correspond to different levels of abstraction by resorting to some form of gradient descent for training via backpropagation. Layers that have been used in deep learning include hidden layers of an artificial neural network and sets of propositional formulas. They may also include latent variables organized layer-wise in deep generative models such as the nodes in deep belief networks and deep boltzmann machines. Deep learning is part of state-of-the-art systems in various disciplines, particularly computer vision, automatic speech recognition (ASR) and human action recognition. The unique features of this book include: • tutorials on deep learning framework with focus on tensor flow, keras etc. • video demonstration of each chapter for enabling the readers to have a good understanding of the chapter contents. • a score of worked out examples on real life applications. • illustrative diagrams • coding examples
In the age of e-society, handwritten signature processing is an enabling technology in a multitude of fields in the "digital agenda" of many countries, ranging from e-health to e-commerce, from e-government to e-justice, from e-democracy to e-banking, and smart cities. Handwritten signatures are very complex signs; they are the result of an elaborate process that depends on the psychophysical state of the signer and the conditions under which the signature apposition process occurs. Notwithstanding, recent efforts from academies and industries now make possible the integration of signature-based technologies into other standard equipment to form complete solutions that are able to support the security requirements of today's society.
Advances in Digital Handwritten Signature Processing primarily provides an update on the most fascinating and valuable researches in the multifaceted field of handwritten signature analysis and processing. The chapters within also introduce and discuss critical aspects and precious opportunities related to the use of this technology, as well as highlight fundamental theoretical and applicative aspects of the field.
This book contains papers by well-recognized and active researchers and scientists, as well as by engineers and commercial managers working for large international companies in the field of signature-based systems for a wide range of applications and for the development of e-society.
This publication is devoted to both researchers and experts active in the field of biometrics and handwriting forensics, as well as professionals involved in the development of signature-based solutions for advanced applications in medicine, finance, commerce, banking, public and private administrations, etc. Handwritten Signature Processing may also be used as an advanced textbook by graduate students.
Автор: Asa Bensten Название: Modern Speech Recognition Approaches ISBN: 1681174618 ISBN-13(EAN): 9781681174617 Издательство: Gazelle Book Services Рейтинг: Цена: 217350.00 T Наличие на складе: Невозможна поставка. Описание: "Voice or speech recognition is the ability of a machine or program to receive and interpret dictation, or to understand and carry out spoken commands. The task of speech recognition is to convert speech into a sequence of words by a computer program. As the most natural communication modality for humans, the ultimate dream of speech recognition is to enable people to communicate more naturally and effectively. Speech recognition is often regarded as the front-end for many NLP components discussed in this book. In practice, the speech system typically uses context-free grammar (CFG) or statistic n-grams for the same reason that hidden Markov models (HMMs) are used for acoustic modelling. Although it initially addressed applications requiring the scanning of audio data for occurrences of particular keywords, the technology has become an effective approach to speech recognition for a wide range of applications. Speech recognition applications are different from any other kind of computer application. It opens up a world of possibilities for developers, especially those building interactive voice responses (IVRs) and other telephony applications, but speech recognition also has some challenges. Speech recognition is also affected by the quality of the input. If a user is calling a system, a bad cell phone connection or overly compressed Internet audio may throw off recognition. Handling these sorts of cases becomes very important when designing speech recognition applications. Modern Speech Recognition Approaches reflect important research on the approaches of speech recognition. The book focuses primarily on speech recognition and the related tasks such as speech enhancement and modelling. Thorough reading of this book will provide comprehensive knowledge on modern speech recognition approaches to the readers. "
Автор: Athanasios Voulodimos, Anastasios Doulamis Название: Recent Advances in 3D Imaging, Modeling, and Reconstruction ISBN: 1799829960 ISBN-13(EAN): 9781799829966 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 134910.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: 3D image reconstruction is used in many fields, such as medicine, entertainment, and computer science. This highly demanded process comes with many challenges, such as images becoming blurry by atmospheric turbulence, getting snowed with noise, or becoming damaged within foreign regions. It is imperative to remain well-informed with the latest research in this field.
Recent Advances in 3D Imaging, Modeling, and Reconstruction is a collection of innovative research on the methods and common techniques of image reconstruction as well as the accuracy of these methods. Featuring coverage on a wide range of topics such as ray casting, holographic techniques, and machine learning, this publication is ideally designed for graphic designers, computer engineers, medical professionals, robotics engineers, city planners, game developers, researchers, academicians, and students.
Автор: Jeremy Knox; Yuchen Wang; Michael Gallagher Название: Artificial Intelligence and Inclusive Education ISBN: 9811381607 ISBN-13(EAN): 9789811381607 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book brings together the fields of artificial intelligence (often known as A.I.) and inclusive education in order to speculate on the future of teaching and learning in increasingly diverse social, cultural, emotional, and linguistic educational contexts. This book addresses a pressing need to understand how future educational practices can promote equity and equality, while at the same time adopting A.I. systems that are oriented towards automation, standardisation and efficiency. The contributions in this edited volume appeal to scholars and students with an interest in forming a critical understanding of the development of A.I. for education, as well as an interest in how the processes of inclusive education might be shaped by future technologies. Grounded in theoretical engagement, establishing key challenges for future practice, and outlining the latest research, this book offers a comprehensive overview of the complex issues arising from the convergence of A.I. technologies and the necessity of developing inclusive teaching and learning.
To date, there has been little in the way of direct association between research and practice in these domains: A.I. has been a predominantly technical field of research and development, and while intelligent computer systems and ‘smart’ software are being increasingly applied in many areas of industry, economics, social life, and education itself, a specific engagement with the agenda of inclusion appears lacking. Although such technology offers exciting possibilities for education, including software that is designed to ‘personalise’ learning or adapt to learner behaviours, these developments are accompanied by growing concerns about the in-built biases involved in machine learning techniques driven by ‘big data’.
Автор: Yanio Hern?ndez Heredia; Vladimir Mili?n N??ez; Jo Название: Progress in Artificial Intelligence and Pattern Recognition ISBN: 3030011313 ISBN-13(EAN): 9783030011314 Издательство: Springer Рейтинг: Цена: 61480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed proceedings of the 6th International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2018, held in Havana, Cuba, in September 2018. The 42 full papers presented were carefully reviewed and selected from 101 submissions. The papers promote and disseminate ongoing research on mathematical methods and computing techniques for artificial intelligence and pattern recognition, in particular in bioinformatics, cognitive and humanoid vision, computer vision, image analysis and intelligent data analysis, as well as their application in a number of diverse areas such as industry, health, robotics, data mining, opinion mining and sentiment analysis, telecommunications, document analysis, and natural language processing and recognition.
Автор: Yong Gao; Nathalie Japkowicz Название: Advances in Artificial Intelligence ISBN: 3642018173 ISBN-13(EAN): 9783642018176 Издательство: Springer Рейтинг: Цена: 65210.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Constitutes the refereed proceedings of the 22nd Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2009, held in Windsor, Canada, in May 2008. This book presents 30 revised full papers together with 5 revised short papers and 8 papers from the graduate student symposium.
Автор: Arturo Hern?ndez Aguirre; Ra?l Monroy Borja; Carlo Название: MICAI 2009: Advances in Artificial Intelligence ISBN: 3642052576 ISBN-13(EAN): 9783642052576 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The Mexican International Conference on Arti?cial Intelligence (MICAI), a yearly international conference organized by the Mexican Society for Arti?cial Intelligence (SMIA), is a major international AI forum and the main event in the academic life of the country's growing AI community. The proceedings of the previous MICAI events were published by Springer in its Lecture Notes in Arti?cial Intelligence (LNAI) series, vol. 1793,2313,2972,3787,4293,4827, and 5317. Since its foundation the conference has been growing in popularity and improving quality. This volume contains the papers presented at the oral sessions of the 8th Mexican International Conference on Arti?cial Intelligence, MICAI 2009, held November 9-13, 2009, in Guanajuato, M xico. The conference received for ev- uation 215 submissions by 646 authors from 21 countries. This volume contains revised versionsof 63 articles, which after thorough and careful revision were- lected by the international Program Committee. Thus the acceptance rate was 29.3% This book is structured into 18 sections, 17 of which correspond to a c- ference track and are representative of the main current areas of interest for the AI community; the remaining section comprises invited papers. The conference featured excellent keynote lectures by leading AI experts: Patricia Melin, Instituto Tecnol gico de Tijuana, M xico Dieter Hutter, DFKI GmbH, Germany Josef Kittler, Surrey University, UK Ram n L pez de Mantaras, IIIA-CSIC, Spain Jos Luis Marroqu n, CIMAT, M xico In addition to the oral technical sessions and keynote lectures, the conf- ence program included tutorials, workshops, and a poster session, which were published in separate proceedings volumes.
Автор: Le Vuong Et Al Название: Face Processing And Applications To Distance Learning ISBN: 9814733024 ISBN-13(EAN): 9789814733021 Издательство: World Scientific Publishing Рейтинг: Цена: 68640.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This special compendium provides a concise and unified vision of facial image processing. It addresses a collection of state-of-the-art techniques, covering the most important areas for facial biometrics and behavior analysis. These techniques also converge to serve an emerging practical application of interactive distance learning.
Readers will get a broad picture of the fundamental science of the field and technical details that make the research interesting. Moreover, the intellectual investigation motivated by the demand of real-life application will make this volume an inspiring read for current and prospective researchers and engineers in the fields of computer vision, machine learning and image processing.
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