Conferences related to Dictionaries

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2016 IEEE International Conference on Image Processing (ICIP)

Signal processing, image processing, biomedical imaging, multimedia, video, multidemensional.


2012 21st International Conference on Pattern Recognition (ICPR)

ICPR is the largest international conference which covers pattern recognition, computer vision, signal processing, and machine learning and their applications. This has been organized every two years by main sponsorship of IAPR, and has recently been with the technical sponsorship of IEEE-CS. The related research fields are also covered by many societies of IEEE including IEEE-CS, therefore the technical sponsorship of IEEE-CS will provide huge benefit to a lot of members of IEEE. Archiving into IEEE Xplore will also provide significant benefit to the all members of IEEE.

  • 2010 20th International Conference on Pattern Recognition (ICPR)

    ICPR 2010 will be an international forum for discussions on recent advances in the fields of Computer Vision; Pattern Recognition and Machine Learning; Signal, Speech, Image and Video Processing; Biometrics and Human Computer Interaction; Multimedia and Document Analysis, Processing and Retrieval; Medical Imaging and Visualization.

  • 2008 19th International Conferences on Pattern Recognition (ICPR)

    The ICPR 2008 will be an international forum for discussions on recent advances in the fields of Computer vision, Pattern recognition (theory, methods and algorithms), Image, speech and signal analysis, Multimedia and video analysis, Biometrics, Document analysis, and Bioinformatics and biomedical applications.


2009 2nd International Symposium on Knowledge Acquisition and Modeling (KAM)

2009 The 2nd International Symposium on Knowledge Acquisition and Modeling (KAM 2009) is concerned with the aspects of Intelligent Information Processing, acquiring, modeling, managing and exploiting knowledge, and the role of these aspects in the construction of knowledge-intensive systems and Intelligent Information services.


2007 22nd International Symposium on Computer and Information Sciences (ISCIS)

The 22nd ISCIS conference will accept research papers in one of the following three tracks: Computer Vision, Graphics and Intelligence - Networks and Systems - Data Management.



Periodicals related to Dictionaries

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Computers, IEEE Transactions on

Design and analysis of algorithms, computer systems, and digital networks; methods for specifying, measuring, and modeling the performance of computers and computer systems; design of computer components, such as arithmetic units, data storage devices, and interface devices; design of reliable and testable digital devices and systems; computer networks and distributed computer systems; new computer organizations and architectures; applications of VLSI ...


Pattern Analysis and Machine Intelligence, IEEE Transactions on

Statistical and structural pattern recognition; image analysis; computational models of vision; computer vision systems; enhancement, restoration, segmentation, feature extraction, shape and texture analysis; applications of pattern analysis in medicine, industry, government, and the arts and sciences; artificial intelligence, knowledge representation, logical and probabilistic inference, learning, speech recognition, character and text recognition, syntactic and semantic processing, understanding natural language, expert systems, ...


Signal Processing Letters, IEEE

Rapid dissemination of new results in signal processing world-wide.


Signal Processing, IEEE Transactions on

The technology of transmission, recording, reproduction, processing, and measurement of speech; other audio-frequency waves and other signals by digital, electronic, electrical, acoustic, mechanical, and optical means; the components and systems to accomplish these and related aims; and the environmental, psychological, and physiological factors of thesetechnologies.




Xplore Articles related to Dictionaries

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A diagnosis method using pseudo-random vectors without intermediate signatures

R. C. Aitken; V. K. Agarwal 1989 IEEE International Conference on Computer-Aided Design. Digest of Technical Papers, 1989

A diagnosis method is proposed which may be used to locate faults in circuits tested with random or pseudorandom test vectors. No intermediate signatures are involved, and the external hardware required is not complex. This proposed diagnosis scheme, called DAPPER, is applicable to multioutput combinational circuits. DAPPER classifies faults initially by their detection probability for coarse resolution, and secondly using ...


Fast algorithm on parameter estimation of wideband LFM signal based on down-chirp and CS

Kang Wang; Wei Ye; Guochao Lao; Yong Wang 2014 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), 2014

Compressed Sensing (CS) has been successfully applied to the parameter estimation of Linear Frequency Modulation (LFM) signal. Compared to the Nyquist sampling method, far less samples are needed to estimate the frequency parameter. However, the super-resolution estimation of frequency parameter can greatly increase the number of atoms in the over-complete dictionary and it will brings a huge amount of computation. ...


Language tweet characteristics of Indonesian citizens

Ahmad Fathan Hidayatullah 2015 International Conference on Science and Technology (TICST), 2015

Indonesia is a wide country which has thousands of islands, hundred languages and dialects. These conditions cause many habits and behaviour to the people, including their activities in social media. Twitter and other social media have no language rules for users. Therefore, people are able to write everything very free without any regulations when they are posting their tweets. Generally, ...


Structured Priors for Sparse-Representation-Based Hyperspectral Image Classification

Xiaoxia Sun; Qing Qu; Nasser M. Nasrabadi; Trac D. Tran IEEE Geoscience and Remote Sensing Letters, 2014

Pixelwise classification, where each pixel is assigned to a predefined class, is one of the most important procedures in hyperspectral image (HSI) analysis. By representing a test pixel as a linear combination of a small subset of labeled pixels, a sparse representation classifier (SRC) gives rather plausible results compared with that of traditional classifiers such as the support vector machine. ...


Using 3G Smartphones for MALL

Wang Yan; Wu Liping 2013 Fourth International Conference on Intelligent Systems Design and Engineering Applications, 2013

Mobile Assisted Language Learning (MALL) is the latest development of Mobile Learning (m-learning) and Computer-assisted Language Learning (CALL). This paper will discuss ways in which 3G smartphones can be used for MALL. The built-in functions of 3G smartphones, along with the various Web Apps and Native Apps that can be used to enhance these functions, provide a wide variety of ...


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Educational Resources on Dictionaries

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eLearning

A diagnosis method using pseudo-random vectors without intermediate signatures

R. C. Aitken; V. K. Agarwal 1989 IEEE International Conference on Computer-Aided Design. Digest of Technical Papers, 1989

A diagnosis method is proposed which may be used to locate faults in circuits tested with random or pseudorandom test vectors. No intermediate signatures are involved, and the external hardware required is not complex. This proposed diagnosis scheme, called DAPPER, is applicable to multioutput combinational circuits. DAPPER classifies faults initially by their detection probability for coarse resolution, and secondly using ...


Fast algorithm on parameter estimation of wideband LFM signal based on down-chirp and CS

Kang Wang; Wei Ye; Guochao Lao; Yong Wang 2014 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), 2014

Compressed Sensing (CS) has been successfully applied to the parameter estimation of Linear Frequency Modulation (LFM) signal. Compared to the Nyquist sampling method, far less samples are needed to estimate the frequency parameter. However, the super-resolution estimation of frequency parameter can greatly increase the number of atoms in the over-complete dictionary and it will brings a huge amount of computation. ...


Language tweet characteristics of Indonesian citizens

Ahmad Fathan Hidayatullah 2015 International Conference on Science and Technology (TICST), 2015

Indonesia is a wide country which has thousands of islands, hundred languages and dialects. These conditions cause many habits and behaviour to the people, including their activities in social media. Twitter and other social media have no language rules for users. Therefore, people are able to write everything very free without any regulations when they are posting their tweets. Generally, ...


Structured Priors for Sparse-Representation-Based Hyperspectral Image Classification

Xiaoxia Sun; Qing Qu; Nasser M. Nasrabadi; Trac D. Tran IEEE Geoscience and Remote Sensing Letters, 2014

Pixelwise classification, where each pixel is assigned to a predefined class, is one of the most important procedures in hyperspectral image (HSI) analysis. By representing a test pixel as a linear combination of a small subset of labeled pixels, a sparse representation classifier (SRC) gives rather plausible results compared with that of traditional classifiers such as the support vector machine. ...


Using 3G Smartphones for MALL

Wang Yan; Wu Liping 2013 Fourth International Conference on Intelligent Systems Design and Engineering Applications, 2013

Mobile Assisted Language Learning (MALL) is the latest development of Mobile Learning (m-learning) and Computer-assisted Language Learning (CALL). This paper will discuss ways in which 3G smartphones can be used for MALL. The built-in functions of 3G smartphones, along with the various Web Apps and Native Apps that can be used to enhance these functions, provide a wide variety of ...


More eLearning Resources

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IEEE-USA E-Books

  • Enabling Technologies

    The Internet gives us access to a wealth of information in languages we don't understand. The investigation of automated or semi-automated approaches to translation has become a thriving research field with enormous commercial potential. This volume investigates how Machine Learning techniques can improve Statistical Machine Translation, currently at the forefront of research in the field. The book looks first at enabling technologies-- technologies that solve problems that are not Machine Translation proper but are linked closely to the development of a Machine Translation system. These include the acquisition of bilingual sentence-aligned data from comparable corpora, automatic construction of multilingual name dictionaries, and word alignment. The book then presents new or improved statistical Machine Translation techniques, including a discriminative training framework for leveraging syntactic information, the use of semi-supervised and kernel-based learning methods, and the combination of multiple Machine Translation outputs in order to improve overall translation quality.ContributorsSrinivas Bangalore, Nicola Cancedda, Josep M. Crego, Marc Dymetman, Jakob Elming, George Foster, Jesús Giménez, Cyril Goutte, Nizar Habash, Gholamreza Haffari, Patrick Haffner, Hitoshi Isahara, Stephan Kanthak, Alexandre Klementiev, Gregor Leusch, Pierre Mahé, Lluís Màrquez, Evgeny Matusov, I. Dan Melamed, Ion Muslea, Hermann Ney, Bruno Pouliquen, Dan Roth, Anoop Sarkar, John Shawe-Taylor, Ralf Steinberger, Joseph Turian, Nicola Ueffing, Masao Utiyama, Zhuoran Wang, Benjamin Wellington, Kenji Yamada

  • Automatic Processing of Bilingual Dictionaries

    This chapter contains sections titled: Bilingual Dictionaries, The ACQUILEX Project, Catizone, Russel, and Warwick, White, Klavans and Tzoukermann, Neff and McCord, The NMSU Computing Research Laboratory, NORM: The CRL Translator's Assistant

  • English-Japanese Machine Translation

    This chapter contains sections titled: Introduction, Dictionaries and Tables, Translation Principles and Flow Diagram, Machine Organization, Conclusion, References

  • Automatic Construction of Multilingual Name Dictionaries

    This chapter contains sections titled: Introduction and Motivation, Related Work, Multilingual Recognition of New Names, Lookup of Known Names and Their Morphological Variants, Evaluation of Person Name Recognition, Identification and Merging of Name Variants, Conclusion and Future Work, Acknowledgments

  • Consumer Projects Using Machine-Readable Dictionaries

    This chapter contains sections titled: The Automatic Creation of Lexical Entries for Machine Translation, Approaches to Achieving Full Specification, Pangloss, Use of Automated Procedures, Slator's PREMO: Knowledge-Based Parsing, IBM: Deciding Attachments

  • Generic Collections: Lists and Dictionaries (C# 2.0) 158

    This chapter contains sections titled: The ICollection<T> Interface, Enumerators and Enumerables, Ordered Values: Comparables and Comparers, The IList<T> Interface, The IDictionary<K,V> Interface, The List<T> Class, The Dictionary<K,V> Class, The Key Value Pair<K,V> Struct Type, The Sorted Dictionary<K,V> Class, The Queue<T> Class, The Stack<T> Class

  • The Present

    This chapter contains sections titled: Piggybacking a Dictionary from a Corpus and a "Seed" MRD, New Modes of Dictionary Construction, Organizational Developments, Conclusion: Evaluating Lexicons?, Is the MRD Era Over?

  • Text Analysis and Its Relationship to Dictionaries: Dictionaries as Texts

    This chapter contains sections titled: The Dictionary as a Text: LDOCE and COBUILD, Dictionaries as Texts, Dictionaries as Knowledge Structures, Text Analysis on a Large Scale, Walker and Amsler, Pathtrieve, Pathfinder Networks

  • Finite-State Morphology: Inflections and Derivations in a Single Framework Using Dictionaries and Rules

    This chapter contains sections titled: Introduction, Towards a Structured Dictionary, MORPHO: a Morphological Analyzer Based on a Dictionary and a Two- Level System, Single Framework for Inflections and Derivations Recognition and Generation, Conclusion, References

  • Query Translation Using Evolutionary Programming for Multi-Lingual Information Retrieval

    Multi-lingual information retrieval (IR) systems apply queries in one language to a document collection in several different languages with the goal of retrieving only those documents relevant to the query. At first glance, deep linguistic analysis and translation of the query appears necessary before retrievals can be performed. IR systems are unique in natural language processing, however, because a pattern of term occurrences in a document generally suffices to determine the subject matter; word order is largely irrelevant. Translated queries are therefore primarily derived by a mapping from a word set in the query language to a word set in the language of the derived query. Large parallel text collections with sentencelevel alignments can provide a baseline for evaluating the correctness of a query translation, but the determination of members of the query translation remains problematic. Constructing a query from machine-readable, bilingual dictionaries and assigning term weights by the evolutionary optimization of a population of potential weighting schemes presents a solution to the difficulties of generating translated queries. In this approach, differences in the rank statistics on the comparative recall results for a query against its native language and its translation against its native language determine the fitness of a tentative query translation.



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