ICPRAM 2012

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.

Each of these tracks 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 tracks:

1. THEORY AND METHODS
2. APPLICATIONS
 

TRACK 1: THEORY AND METHODS

• Exact and Approximate Inference
• Density Estimation
• Bayesian Models
• Gaussian Processes
• Model Selection
• Graphical and Graph-based Models
• Missing Data
• Ensemble Methods
• Neural Networks
• Kernel Methods
• Large Margin Methods
• Classification
• Regression
• Sparsity
• Feature Selection and Extraction
• Spectral Methods
• Embedding and Manifold Learning
• Similarity and Distance Learning
• Matrix Factorization
• Clustering
• ICA, PCA, CCA and other Linear Models
• Fuzzy Logic
• Active Learning
• Cost-sensitive Learning
• Incremental Learning
• On-line Learning
• Structured Learning
• Multi-agent Learning
• Multi-instance Learning
• Reinforcement Learning
• Instance-based Learning
• Knowledge Acquisition and Representation
• Meta Learning
• Multi-strategy Learning
• Case-based Reasoning
• Inductive Learning
• Computational Learning Theory
• Cooperative Learning
• Evolutionary Computation
• Information Retrieval and Learning
• Hybrid Learning Algorithms
• Planning and Learning
• Convex Optimization
• Stochastic Methods
• Combinatorial Optimization

TRACK 2: APPLICATIONS

• Natural Language Processing
• Information Retrieval
• Ranking
• Web Applications
• Economics, Business and Forecasting Applications
• Bioinformatics and Systems Biology
• Audio and Speech Processing
• Signal Processing
• Image Understanding
• Sensors and Early Vision
• Motion and Tracking
• Image-based Modelling
• Shape Representation
• Object Recognition
• Video Analysis
• Medical Imaging
• Learning and Adaptive Control
• Perception
• Learning in Process Automation
• Learning of Action Patterns
• Virtual Environments
• Robotics