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Author: El?bieta P?kalska
Publisher: World Scientific
ISBN: 9812565302
Category : Computers
Languages : en
Pages : 636
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Book Description
This book provides a fundamentally new approach to pattern recognition in which objects are characterized by relations to other objects instead of by using features or models. This 'dissimilarity representation' bridges the gap between the traditionally opposing approaches of statistical and structural pattern recognition.Physical phenomena, objects and events in the world are related in various and often complex ways. Such relations are usually modeled in the form of graphs or diagrams. While this is useful for communication between experts, such representation is difficult to combine and integrate by machine learning procedures. However, if the relations are captured by sets of dissimilarities, general data analysis procedures may be applied for analysis.With their detailed description of an unprecedented approach absent from traditional textbooks, the authors have crafted an essential book for every researcher and systems designer studying or developing pattern recognition systems.
Author: El?bieta P?kalska
Publisher: World Scientific
ISBN: 9812565302
Category : Computers
Languages : en
Pages : 636
Get Book Here
Book Description
This book provides a fundamentally new approach to pattern recognition in which objects are characterized by relations to other objects instead of by using features or models. This 'dissimilarity representation' bridges the gap between the traditionally opposing approaches of statistical and structural pattern recognition.Physical phenomena, objects and events in the world are related in various and often complex ways. Such relations are usually modeled in the form of graphs or diagrams. While this is useful for communication between experts, such representation is difficult to combine and integrate by machine learning procedures. However, if the relations are captured by sets of dissimilarities, general data analysis procedures may be applied for analysis.With their detailed description of an unprecedented approach absent from traditional textbooks, the authors have crafted an essential book for every researcher and systems designer studying or developing pattern recognition systems.
Author: Robert P W Duin
Publisher: World Scientific
ISBN: 9814479144
Category : Computers
Languages : en
Pages : 634
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Book Description
This book provides a fundamentally new approach to pattern recognition in which objects are characterized by relations to other objects instead of by using features or models. This 'dissimilarity representation' bridges the gap between the traditionally opposing approaches of statistical and structural pattern recognition.Physical phenomena, objects and events in the world are related in various and often complex ways. Such relations are usually modeled in the form of graphs or diagrams. While this is useful for communication between experts, such representation is difficult to combine and integrate by machine learning procedures. However, if the relations are captured by sets of dissimilarities, general data analysis procedures may be applied for analysis.With their detailed description of an unprecedented approach absent from traditional textbooks, the authors have crafted an essential book for every researcher and systems designer studying or developing pattern recognition systems.
Author: Indranath Chatterjee
Publisher: John Wiley & Sons
ISBN: 1394173342
Category : Computers
Languages : en
Pages : 244
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Book Description
Machine Learning Applications Practical resource on the importance of Machine Learning and Deep Learning applications in various technologies and real-world situations Machine Learning Applications discusses methodological advancements of machine learning and deep learning, presents applications in image processing, including face and vehicle detection, image classification, object detection, image segmentation, and delivers real-world applications in healthcare to identify diseases and diagnosis, such as creating smart health records and medical imaging diagnosis, and provides real-world examples, case studies, use cases, and techniques to enable the reader’s active learning. Composed of 13 chapters, this book also introduces real-world applications of machine and deep learning in blockchain technology, cyber security, and climate change. An explanation of AI and robotic applications in mechanical design is also discussed, including robot-assisted surgeries, security, and space exploration. The book describes the importance of each subject area and detail why they are so important to us from a societal and human perspective. Edited by two highly qualified academics and contributed to by established thought leaders in their respective fields, Machine Learning Applications includes information on: Content based medical image retrieval (CBMIR), covering face and vehicle detection, multi-resolution and multisource analysis, manifold and image processing, and morphological processing Smart medicine, including machine learning and artificial intelligence in medicine, risk identification, tailored interventions, and association rules AI and robotics application for transportation and infrastructure (e.g., autonomous cars and smart cities), along with global warming and climate change Identifying diseases and diagnosis, drug discovery and manufacturing, medical imaging diagnosis, personalized medicine, and smart health records With its practical approach to the subject, Machine Learning Applications is an ideal resource for professionals working with smart technologies such as machine and deep learning, AI, IoT, and other wireless communications; it is also highly suitable for professionals working in robotics, computer vision, cyber security and more.
Author: Yanio Hernández Heredia
Publisher: Springer
ISBN: 3030011321
Category : Computers
Languages : en
Pages : 391
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Book Description
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.
Author: Niels da Vitoria Lobo
Publisher: Springer
ISBN: 3540896899
Category : Computers
Languages : en
Pages : 1029
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Book Description
This volume in the Springer Lecture Notes in Computer Science (LNCS) series contains 98 papers presented at the S+SSPR 2008 workshops. S+SSPR 2008 was the sixth time that the SPR and SSPR workshops organized by Technical Committees, TC1 and TC2, of the International Association for Pattern Rec- nition (IAPR) wereheld as joint workshops. S+SSPR 2008was held in Orlando, Florida, the family entertainment capital of the world, on the beautiful campus of the University of Central Florida, one of the up and coming metropolitan universities in the USA. S+SSPR 2008 was held during December 4–6, 2008 only a few days before the 19th International Conference on Pattern Recog- tion(ICPR2008),whichwasheldin Tampa,onlytwo hoursawayfromOrlando, thus giving the opportunity of both conferences to attendees to enjoy the many attractions o?ered by two neighboring cities in the state of Florida. SPR 2008 and SSPR 2008 received a total of 175 paper submissions from many di?erent countries around the world, thus giving the workshop an int- national clout, as was the case for past workshops. This volume contains 98 accepted papers: 56 for oral presentations and 42 for poster presentations. In addition to parallel oral sessions for SPR and SSPR, there was also one joint oral session with papers of interest to both the SPR and SSPR communities. A recent trend that has emerged in the pattern recognition and machine lea- ing research communities is the study of graph-based methods that integrate statistical andstructural approaches.
Author: Marcello Pelillo
Publisher: Springer Science & Business Media
ISBN: 364224470X
Category : Computers
Languages : en
Pages : 345
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Book Description
This book constitutes the proceedings of the First International Workshop on Similarity Based Pattern Recognition, SIMBAD 2011, held in Venice, Italy, in September 2011. The 16 full papers and 7 poster papers presented were carefully reviewed and selected from 35 submissions. The contributions are organized in topical sections on dissimilarity characterization and analysis; generative models of similarity data; graph-based and relational models; clustering and dissimilarity data; applications; spectral methods and embedding.
Author: Edwin Hancock
Publisher: Springer
ISBN: 3642391400
Category : Computers
Languages : en
Pages : 307
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Book Description
This book constitutes the proceedings of the Second International Workshop on Similarity Based Pattern Analysis and Recognition, SIMBAD 2013, which was held in York, UK, in July 2013. The 18 papers presented were carefully reviewed and selected from 33 submissions. They cover a wide range of problems and perspectives, from supervised to unsupervised learning, from generative to discriminative models, from theoretical issues to real-world practical applications, and offer a timely picture of the state of the art in the field.
Author: Pasi Fränti
Publisher: Springer
ISBN: 3662444151
Category : Computers
Languages : en
Pages : 493
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Book Description
This book constitutes the proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2014; comprising the International Workshop on Structural and Syntactic Pattern Recognition, SSPR, and the International Workshop on Statistical Techniques in Pattern Recognition, SPR. The total of 25 full papers and 22 poster papers included in this book were carefully reviewed and selected from 78 submissions. They are organized in topical sections named: graph kernels; clustering; graph edit distance; graph models and embedding; discriminant analysis; combining and selecting; joint session; metrics and dissimilarities; applications; partial supervision; and poster session.
Author: Burgos, Diego Alexander Tibaduiza
Publisher: IGI Global
ISBN: 1799818411
Category : Computers
Languages : en
Pages : 357
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Book Description
The implementation of data and information analysis has become a trending solution within multiple professions. New tools and approaches are continually being developed within data analysis to further solve the challenges that come with professional strategy. Pattern recognition is an innovative method that provides comparison techniques and defines new characteristics within the information acquisition process. Despite its recent trend, a considerable amount of research regarding pattern recognition and its various strategies is lacking. Pattern Recognition Applications in Engineering is an essential reference source that discusses various strategies of pattern recognition algorithms within industrial and research applications and provides examples of results in different professional areas including electronics, computation, and health monitoring. Featuring research on topics such as condition monitoring, data normalization, and bio-inspired developments, this book is ideally designed for analysts; researchers; civil, mechanical, and electronic engineers; computing scientists; chemists; academicians; and students.
Author: Nadia Mana
Publisher: Springer
ISBN: 3642332129
Category : Computers
Languages : en
Pages : 253
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Book Description
This book constitutes the refereed proceedings of the 5th INNS IAPR TC3 GIRPR International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2012, held in Trento, Italy, in September 2012. The 21 revised full papers presented were carefully reviewed and selected for inclusion in this volume. They cover a large range of topics in the field of neural network- and machine learning-based pattern recognition presenting and discussing the latest research, results, and ideas in these areas.
