6th International Conference on Pattern Recognition Applications and Methods
When : 2017-02-24
Where : Porto,Portugal
Submission Deadline : 2016-10-04
Categories : Networks & Communications , Digital Signal & Image Processing
6th International Conference on Pattern Recognition Applications and Methods
(ICPRAM 2017)
24th - 26th February,2017
Porto, Portugal
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.
Topics
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
2. APPLICATIONS
AREA 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
- Multiclassifier Fusion
AREA 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
- Biometrics
