Similarity-Based Pattern Recognition

Similarity-Based Pattern Recognition PDF Author:
Publisher:
ISBN: 9783642244728
Category :
Languages : en
Pages : 348

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Book Description

Similarity-Based Pattern Recognition

Similarity-Based Pattern Recognition PDF Author:
Publisher:
ISBN: 9783642244728
Category :
Languages : en
Pages : 348

Get Book Here

Book Description


Similarity-Based Pattern Analysis and Recognition

Similarity-Based Pattern Analysis and Recognition PDF Author: Marcello Pelillo
Publisher: Springer Science & Business Media
ISBN: 1447156285
Category : Computers
Languages : en
Pages : 293

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Book Description
This accessible text/reference presents a coherent overview of the emerging field of non-Euclidean similarity learning. The book presents a broad range of perspectives on similarity-based pattern analysis and recognition methods, from purely theoretical challenges to practical, real-world applications. The coverage includes both supervised and unsupervised learning paradigms, as well as generative and discriminative models. Topics and features: explores the origination and causes of non-Euclidean (dis)similarity measures, and how they influence the performance of traditional classification algorithms; reviews similarity measures for non-vectorial data, considering both a “kernel tailoring” approach and a strategy for learning similarities directly from training data; describes various methods for “structure-preserving” embeddings of structured data; formulates classical pattern recognition problems from a purely game-theoretic perspective; examines two large-scale biomedical imaging applications.

Similarity-Based Pattern Recognition

Similarity-Based Pattern Recognition PDF 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.

Similarity-Based Pattern Recognition

Similarity-Based Pattern Recognition PDF Author: Aasa Feragen
Publisher: Springer
ISBN: 331924261X
Category : Computers
Languages : en
Pages : 238

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Book Description
This book constitutes the proceedings of the Third International Workshop on Similarity Based Pattern Analysis and Recognition, SIMBAD 2015, which was held in Copenahgen, Denmark, in October 2015. The 15 full and 8 short papers presented were carefully reviewed and selected from 30 submissions.The workshop focus on problems, techniques, applications, and perspectives: from supervisedto unsupervised learning, from generative to discriminative models, and fromtheoretical issues to empirical validations.

Similarity-Based Pattern Recognition

Similarity-Based Pattern Recognition PDF Author: Marcello Pelillo
Publisher: Springer
ISBN: 3642244718
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.

Special Issue Similarity Based Pattern Recognition

Special Issue Similarity Based Pattern Recognition PDF Author: Manuele Bicego
Publisher:
ISBN:
Category :
Languages : en
Pages : 136

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Book Description


Similarity-Based Pattern Recognition

Similarity-Based Pattern Recognition PDF Author: Aasa Feragen
Publisher:
ISBN: 9783319242620
Category :
Languages : en
Pages :

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Book Description
This book constitutes the proceedings of the Third International Workshop on Similarity Based Pattern Analysis and Recognition, SIMBAD 2015, which was held in Copenahgen, Denmark, in October 2015. The 15 full and 8 short papers presented were carefully reviewed and selected from 30 submissions.The workshop focus on problems, techniques, applications, and perspectives: from supervised to unsupervised learning, from generative to discriminative models, and from theoretical issues to empirical validations.

Similarity-Based Pattern Recognition

Similarity-Based Pattern Recognition PDF 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.

Machine Learning and Data Mining in Pattern Recognition

Machine Learning and Data Mining in Pattern Recognition PDF Author: Petra Perner
Publisher: Springer
ISBN: 3540450653
Category : Computers
Languages : en
Pages : 452

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Book Description
TheInternationalConferenceonMachineLearningandDataMining(MLDM)is the third meeting in a series of biennial events, which started in 1999, organized by the Institute of Computer Vision and Applied Computer Sciences (IBaI) in Leipzig. MLDM began as a workshop and is now a conference, and has brought the topic of machine learning and data mining to the attention of the research community. Seventy-?ve papers were submitted to the conference this year. The program committeeworkedhardtoselectthemostprogressiveresearchinafairandc- petent review process which led to the acceptance of 33 papers for presentation at the conference. The 33 papers in these proceedings cover a wide variety of topics related to machine learning and data mining. The two invited talks deal with learning in case-based reasoning and with mining for structural data. The contributed papers can be grouped into nine areas: support vector machines; pattern dis- very; decision trees; clustering; classi?cation and retrieval; case-based reasoning; Bayesian models and methods; association rules; and applications. We would like to express our appreciation to the reviewers for their precise andhighlyprofessionalwork.WearegratefultotheGermanScienceFoundation for its support of the Eastern European researchers. We appreciate the help and understanding of the editorial sta? at Springer Verlag, and in particular Alfred Hofmann,whosupportedthepublicationoftheseproceedingsintheLNAIseries. Last, but not least, we wish to thank all the speakers and participants who contributed to the success of the conference.

Similarity Measures for Face Recognition

Similarity Measures for Face Recognition PDF Author: Enrico Vezzetti
Publisher: Bentham Science Publishers
ISBN: 1681080443
Category : Computers
Languages : en
Pages : 108

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Book Description
Face recognition has several applications, including security, such as (authentication and identification of device users and criminal suspects), and in medicine (corrective surgery and diagnosis). Facial recognition programs rely on algorithms that can compare and compute the similarity between two sets of images. This eBook explains some of the similarity measures used in facial recognition systems in a single volume. Readers will learn about various measures including Minkowski distances, Mahalanobis distances, Hansdorff distances, cosine-based distances, among other methods. The book also summarizes errors that may occur in face recognition methods. Computer scientists "facing face" and looking to select and test different methods of computing similarities will benefit from this book. The book is also useful tool for students undertaking computer vision courses.