Marinai simone (33 Ergebnisse)

2004. 16 x 24 cm. XII, 568 S. XII, 568 p. softcover Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. (Lecture Notes in Computer Science). Sprache: Englisch.…

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Hardcover. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Paperback. Zustand: Brand New. 2008 edition. 318 pages. 9.21x6.14x0.87 inches. In Stock.

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Kartoniert / Broschiert. Zustand: New.

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the thoroughly refereed proceedings of the 12th Italian Research Conference on Digital Libraries, IRCDL 2016, held in Firence, Italy, in February 2016.The 15 papers presented were carefully selected from 23 submissions and cover topics such as formal methods, long-term preservation, metadata creation, management and curation, multimedia, ontology and linked data.The papers deal with numerous multidisciplinary aspects ranging from computer science to humanities in the broader sense, including research areas such as archival and library information sciences; information management systems; semantic technologies; information retrieval; new knowledge environments.…

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - TheThirdIAPRTC3WorkshoponArti cialNeuralNetworksinPatternRec- nition, ANNPR 2008, was held at Pierre and Marie Curie University in Paris (France), July 2 4, 2008. The workshop was organized by the Technical C- mittee on Neural Networks and Computational Intelligence (TC3) that is one of the 20 TCs of the International Association for Pattern Recognition (IAPR). The scope of TC3 includes computational intelligence approaches, such as fuzzy systems, evolutionary computing and arti cial neural networks and their use in various pattern recognition applications. ANNPR 2008 followed the success of the previous workshops: ANNPR 2003 held at the University of Florence (Italy) andANPPR 2006held at ReisensburgCastle, Universityof Ulm (Germany).All the workshops featured a single-track program including both oral sessions and posters with a focus on active participation from every participant. Inrecentyears,the eld ofneuralnetworkshasmaturedconsiderablyinboth methodologyandreal-worldapplications.Asre ectedinthisbook,arti cialn- ral networks in pattern recognition combine many ideas from machine learning, advanced statistics, signal and image processing for solving complex real-world pattern recognition problems. High quality across such a diverse eld of research can only be achieved through a rigorous and selective review process. For this workshop, 57 papers were submitted out of which 29 were selected for inclusion in the proceedings. The oral sessions included 18 papers, while 11 contributions were presented as posters. ANNPR 2008 featured research works in the areas of supervised and unsupervised learning, multiple classi er systems, pattern recognition in signal and image processing, and feature selection.…

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Thisvolumecontainspapersselectedforpresentationatthe6thIAPRWorkshop on Document Analysis Systems (DAS 2004) held during September 8-10, 2004 at the University of Florence, Italy. Several papers represent the state of the art in a broad range of 'traditional' topics such as layout analysis, applications to graphics recognition, and handwritten documents. Other contributions address the description of complete working systems, which is one of the strengths of this workshop. Some papers extend the application domains to other media, like the processing of Internet documents. The peculiarity of this 6th workshop was the large number of papers related to digital libraries and to the processing of historical documents, a taste which frequently requires the analysis of color documents. A total of 17 papers are associated with these topics, whereas two yearsago (in DAS 2002) only a couple of papers dealt with these problems. In our view there are three main reasons for this new wave in the DAScommunity. From the scienti c point of view, several research elds reached a thorough knowledge of techniques and problems that can be e ectively solved, and this expertise can now be applied to new domains. Another incentive has been provided by several research projects funded by the EC and the NSF on topics related to digital libraries.…

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Unsupervised Learning.- Simple and Effective Connectionist Nonparametric Estimation of Probability Density Functions.- Comparison Between Two Spatio-Temporal Organization Maps for Speech Recognition.- Adaptive Feedback Inhibition Improves Pattern Discrimination Learning.- Semi-supervised Learning.- Supervised Batch Neural Gas.- Fuzzy Labeled Self-Organizing Map with Label-Adjusted Prototypes.- On the Effects of Constraints in Semi-supervised Hierarchical Clustering.- A Study of the Robustness of KNN Classifiers Trained Using Soft Labels.- Supervised Learning.- An Experimental Study on Training Radial Basis Functions by Gradient Descent.- A Local Tangent Space Alignment Based Transductive Classification Algorithm.- Incremental Manifold Learning Via Tangent Space Alignment.- A Convolutional Neural Network Tolerant of Synaptic Faults for Low-Power Analog Hardware.- Ammonium Estimation in a Biological Wastewater Plant Using Feedforward Neural Networks.- Support Vector Learning.- Support Vector Regression Using Mahalanobis Kernels.- Incremental Training of Support Vector Machines Using Truncated Hypercones.- Fast Training of Linear Programming Support Vector Machines Using Decomposition Techniques.- Multiple Classifier Systems.- Multiple Classifier Systems for Embedded String Patterns.- Multiple Neural Networks for Facial Feature Localization in Orientation-Free Face Images.- Hierarchical Neural Networks Utilising Dempster-Shafer Evidence Theory.- Combining MF Networks: A Comparison Among Statistical Methods and Stacked Generalization.- Visual Object Recognition.- Object Detection and Feature Base Learning with Sparse Convolutional Neural Networks.- Visual Classification of Images by Learning Geometric Appearances Through Boosting.- An Eye Detection System Based on Neural Autoassociators.- Orientation Histograms for Face Recognition.- Data Mining in Bioinformatics.- An Empirical Comparison of Feature Reduction Methods in the Context of Microarray Data Classification.- Unsupervised Feature Selection for Biomarker Identification in Chromatography and Gene Expression Data.- Learning and Feature Selection Using the Set Covering Machine with Data-Dependent Rays on Gene Expression Profiles.…

Zustand: New. Proceedings of the Second IAPR Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2006Presents 26 revised papersCoverage includes unsupervised learning, semi-supervised learning, supervised learning, support vector learnin.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.…

Paperback. Zustand: Brand New. 178 pages. 9.25x6.25x0.50 inches. In Stock.

Taschenbuch. Zustand: Neu. Artificial Neural Networks in Pattern Recognition | Second IAPR Workshop, ANNPR 2006, Ulm, Germany, August 31-September 2, 2006, Proceedings | Friedhelm Schwenker (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2006 | Springer | EAN 9783540379515 | Verantwortliche Person für die EU: Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg, productsafety[at]springernature[dot]com | Anbieter: preigu.…

Taschenbuch. Zustand: Neu. Artificial Neural Networks in Pattern Recognition | Third IAPR TC3 Workshop, ANNPR 2008 Paris, France, July 2-4, 2008, Proceedings | Lionel Prevost (u. a.) | Taschenbuch | ix | Englisch | 2008 | Springer | EAN 9783540699385 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Taschenbuch. Zustand: Neu. Digital Libraries and Multimedia Archives | 12th Italian Research Conference on Digital Libraries, IRCDL 2016, Florence, Italy, February 4-5, 2016, Revised Selected Papers | Maristella Agosti (u. a.) | Taschenbuch | Communications in Computer and Information Science | x | Englisch | 2017 | Springer | EAN 9783319562995 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 318 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Zustand: Used. pp. 448 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.

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Taschenbuch. Zustand: Neu. Machine Learning in Document Analysis and Recognition | Simone Marinai (u. a.) | Taschenbuch | Studies in Computational Intelligence | xii | Englisch | 2010 | Springer | EAN 9783642095115 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphicalcomponents of a document and to extract information. With rst papers dating back to the 1960's, DAR is a mature but still gr- ing research eld with consolidated and known techniques. Optical Character Recognition (OCR) engines are some of the most widely recognized pr- ucts of the research in this eld, while broader DAR techniques are nowadays studied and applied to other industrial and o ce automation systems. In the machine learning community, one of the most widely known - search problems addressed in DAR is recognition of unconstrained handwr- ten characters which has been frequently used in the past as a benchmark for evaluating machine learning algorithms, especially supervised classi ers. However, developing a DAR system is a complex engineering task that involves the integration of multiple techniques into an organic framework. A reader may feel that the use of machine learning algorithms is not approp- ate for other DAR tasks than character recognition. On the contrary, such algorithms have been massively used for nearly all the tasks in DAR. With large emphasis being devoted to character recognition and word recognition, other tasks such as pre-processing, layout analysis, character segmentation, and signature veri cation have also bene ted much from machine learning algorithms. …

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphicalcomponents of a document and to extract information. With rst papers dating back to the 1960's, DAR is a mature but still gr- ing research eld with consolidated and known techniques. Optical Character Recognition (OCR) engines are some of the most widely recognized pr- ucts of the research in this eld, while broader DAR techniques are nowadays studied and applied to other industrial and o ce automation systems. In the machine learning community, one of the most widely known - search problems addressed in DAR is recognition of unconstrained handwr- ten characters which has been frequently used in the past as a benchmark for evaluating machine learning algorithms, especially supervised classi ers. However, developing a DAR system is a complex engineering task that involves the integration of multiple techniques into an organic framework. A reader may feel that the use of machine learning algorithms is not approp- ate for other DAR tasks than character recognition. On the contrary, such algorithms have been massively used for nearly all the tasks in DAR. With large emphasis being devoted to character recognition and word recognition, other tasks such as pre-processing, layout analysis, character segmentation, and signature veri cation have also bene ted much from machine learning algorithms.…

Paperback. Zustand: Brand New. 434 pages. 9.25x6.10x1.01 inches. In Stock.