Call for papers. Please distribute.

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Current Trends in Computer Science

Morelia, México

http://enc.smcc.org.mx/current-trends

Important Dates

    * Paper Submissions Due: May 4, 2007
    * Notification of Acceptance: June 4, 2007
    * Camera Ready Versions Due: July 9, 2007
    * Author Registration Deadline: July 9, 2007
    * Early Registration Deadline: August 20, 2007
    * Conference: September 26-28, 2007


The Mexican Computer Science Society organizes a yearly meeting
gathering researchers, students, educators and industry leaders for a
week. This meeting is a multiconference with many workshops,
tutorials, international conferences and student activities. The
international conference Current Trends in Computer Science is a
multi-track conference around a hot topic for the Mexican research
community. This year the trend/topic is information processing and
retrieval from three points of view. The first track is about
classical information retrieval and the web with standard methods. The
second track focuses on data analysis and management, that is, the
frontier between pattern recognition and databases, where large-scale
applications need to handle and retrieve multimedia and complex
objects. The third track focuses on the user-driven software systems
motivated by the above problems.


Tracks

    * Information Retrieval
    * Scalable Pattern Recognition
    * User Centered Software Systems


Track: Scalable Pattern Recognition

Chair:

Gonzalo Navarro (Universidad de Chile, Chile)

Introduction

Pattern recognition and content-based object retrieval share a large
number of characteristics but are usually addressed from different
communities. The pattern recognition community proposes feature
extraction and classification techniques that are tested in
small-scale scenarios (a few thousand objects are enough to determine
if a feature or classifier is worth to be pursued). On the other hand,
the database community looks for the technology to access (very) large
repositories of objects modeled as high-dimensional vector spaces, or
as metric spaces.

The aim of this track is to bring together researchers from both
communities, focusing especially on the problem posed by applications
that need to handle and retrieve objects from massive databases.
Papers where extraction and classification techniques are proposed and
examined under the light of the efficiency that can be achieved for
massive data sets, or where efficient access methods are proposed for
existing pattern recognition techniques, are especially welcome.

The topics of this conference include

    * pattern recognition
    * feature extraction and signal processing
    * scalable classifiers
    * image processing
    * audio processing
    * data clustering
    * streams and stream-based signal processing
    * metric indexes
    * high dimensional access methods
    * implementation of multimedia databases
    * efficient similarity searching


Invited Speaker

Hanan Samet, University of Maryland.

Program Committee

Sebastiano Battiato, Universitá di Catania, Italy
Carlos Brizuela, CICESE, Mexico
Benjamin Bustos, Universidad de Chile,
Edgar Chávez, Universidad Michoacana/CIMAT, Mexico
Paolo Ciaccia, Universitá di Bologna, Italy.
Arturo Hernandez CIMAT, Mexico
Tin Kam Ho, Bell Labs Research, USA.
Jose Luis Marroquin, CIMAT, Mexico
José Martinez Trinidad INAOE, Mexico
Daniel Miranker, University of Texas at Austin, USA.
David Mount, University of Maryland, USA.
Arlindo Oliveira, INESC Lisboa, Portugal.
Marco Patella, Universitá di Bologna, Italy.
Hanan Samet, University of Maryland.
Tomas Skopal, Charles University, Prague, Czech Republic
Enrique Vidal, Universidad Politécnica de Valencia,
Pavel Zezula, Masaryk University, Czech Republic.

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