MLPRA 2012 - International Workshop on Machine Learning, Pattern Recognition & Applications (MLPRA 2012)
Topics/Call fo Papers
The International Workshop on Machine Learning, Pattern Recognition and Applications aims to bring together researchers in the fields of Machine Learning and Pattern Recognition. The workshop will address recent advances in theory, methodologies and various related applications. It is meant to promote the advancement, discussion and presentation of new research and development in the areas of machine learning, pattern recognition and applications.
The Workshop topics of interest include (but are not limited to) the following:
Statistical Learning
Knowledge Acquisition and Learning
Knowledge Discovery
Cooperative Learning
Support Vector Machines
Instance Based Learning
Grammatical Inference
Computational Learning Theory
Neural Network Learning
Object, Character, Graphical and Text Recognition
Multi-classifiers
Neural Networks for Pattern Recognition
Fuzzy Methods for Pattern Recognition
Syntactical Methods
Statistical Methods
Structural Methods
Logical and Combinatorial Methods
Classification
Feature Selection and Extraction
Clustering, Descriptors, Segmentation, and Filtering
Matching & Verification
Computer Vision
Image Understanding, Description and Recognition
Machine Learning & Pattern Recognition Applications
INSTRUCTIONS FOR AUTHORS:
You are invited to submit original and unpublished research works on above and other topics related to machine learning, pattern recognition and applications. Submitted papers must not have been published or simultaneously submitted elsewhere. Submission should include a cover page with authors' names, affiliation addresses, fax numbers, phone numbers, and email addresses. Please, indicate clearly the corresponding author and include up to 6 keywords from the above list of topics and an abstract of no more than 400 words. The full manuscript should be at most 7 pages using the two-column IEEE format. Additional pages will be charged additional fee. Short papers (up to 4 pages), poster papers and posters (please refer to http://hpcs2012.cisedu.info/home/posters for the submission details) will also be accepted for submission. Please include page numbers on all preliminary submissions to make it easier for reviewers to provide helpful comments.
Submit a PDF copy of your full manuscript via email to the Workshop organizers at valev-AT-math.bas.bg and vzeljkov-AT-nyit.edu. Submissions will be acknowledged within 48 hours.
Only PDF files will be accepted, sent by email to the workshop organizers. Each paper will receive a minimum of three reviews. Papers will be selected based on their originality, relevance, technical clarity and presentation. Submission implies the willingness of at least one of the authors to register and present the paper, if accepted. Authors of accepted papers must guarantee that their papers will be registered and presented at the workshop.
Accepted papers will be published in the Conference proceedings. Instructions for final manuscript format and requirements will be posted on the HPCS 2012 Conference web site. It is our intent to have the proceedings formally published in hard and soft copies and be available at the time of the conference. The proceedings is projected to be included in the IEEE Digital Library and indexed accordingly.
The Workshop topics of interest include (but are not limited to) the following:
Statistical Learning
Knowledge Acquisition and Learning
Knowledge Discovery
Cooperative Learning
Support Vector Machines
Instance Based Learning
Grammatical Inference
Computational Learning Theory
Neural Network Learning
Object, Character, Graphical and Text Recognition
Multi-classifiers
Neural Networks for Pattern Recognition
Fuzzy Methods for Pattern Recognition
Syntactical Methods
Statistical Methods
Structural Methods
Logical and Combinatorial Methods
Classification
Feature Selection and Extraction
Clustering, Descriptors, Segmentation, and Filtering
Matching & Verification
Computer Vision
Image Understanding, Description and Recognition
Machine Learning & Pattern Recognition Applications
INSTRUCTIONS FOR AUTHORS:
You are invited to submit original and unpublished research works on above and other topics related to machine learning, pattern recognition and applications. Submitted papers must not have been published or simultaneously submitted elsewhere. Submission should include a cover page with authors' names, affiliation addresses, fax numbers, phone numbers, and email addresses. Please, indicate clearly the corresponding author and include up to 6 keywords from the above list of topics and an abstract of no more than 400 words. The full manuscript should be at most 7 pages using the two-column IEEE format. Additional pages will be charged additional fee. Short papers (up to 4 pages), poster papers and posters (please refer to http://hpcs2012.cisedu.info/home/posters for the submission details) will also be accepted for submission. Please include page numbers on all preliminary submissions to make it easier for reviewers to provide helpful comments.
Submit a PDF copy of your full manuscript via email to the Workshop organizers at valev-AT-math.bas.bg and vzeljkov-AT-nyit.edu. Submissions will be acknowledged within 48 hours.
Only PDF files will be accepted, sent by email to the workshop organizers. Each paper will receive a minimum of three reviews. Papers will be selected based on their originality, relevance, technical clarity and presentation. Submission implies the willingness of at least one of the authors to register and present the paper, if accepted. Authors of accepted papers must guarantee that their papers will be registered and presented at the workshop.
Accepted papers will be published in the Conference proceedings. Instructions for final manuscript format and requirements will be posted on the HPCS 2012 Conference web site. It is our intent to have the proceedings formally published in hard and soft copies and be available at the time of the conference. The proceedings is projected to be included in the IEEE Digital Library and indexed accordingly.
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Last modified: 2012-02-14 18:24:59