ICPRAM 2017 : International Conference on Pattern Recognition Applications and Methods
Conference Series : International Conference on Pattern Recognition Applications and Methods
Call For Papers
The International Conference on Pattern Recognition Applications and Methods would like to become a major point of contact between researchers, engineers and practitioners on the areas of Pattern Recognition, both from theoretical and application perspectives.
Contributions describing applications of Pattern Recognition techniques to real-world problems, interdisciplinary research, experimental and/or theoretical studies yielding new insights that advance Pattern Recognition methods are especially encouraged.
Papers describing original work are invited in any of the areas listed below. Accepted papers, presented at the conference by one of the authors, will be published in the proceedings of ICPRAM with an ISBN. Acceptance will be based on quality, relevance and originality. There will be both oral and poster sessions.
Special sessions, dedicated to case-studies and commercial presentations, as well as technical tutorials, dedicated to technical/scientific topics, are also envisaged: companies interested in presenting their products/methodologies or researchers interested in presenting a demo or lecturing a tutorial are invited to contact the conference secretariat.
Each of these topic areas is expanded below but the sub-topics list is not exhaustive. Papers may address one or more of the listed sub-topics, although authors should not feel limited by them. Unlisted but related sub-topics are also acceptable, provided they fit in one of the following main topic areas:
1. THEORY AND METHODS
AREA 1: THEORY AND METHODS
Exact and Approximate Inference
Graphical and Graph-based Models
Large Margin Methods
Feature Selection and Extraction
Embedding and Manifold Learning
Similarity and Distance Learning
ICA, PCA, CCA and other Linear Models
Knowledge Acquisition and Representation
Computational Learning Theory
Information Retrieval and Learning
Hybrid Learning Algorithms
Planning and Learning
AREA 2: APPLICATIONS
Natural Language Processing
Economics, Business and Forecasting Applications
Bioinformatics and Systems Biology
Audio and Speech Processing
Sensors and Early Vision
Motion and Tracking
Learning and Adaptive Control
Learning in Process Automation
Learning of Action Patterns