IEEE Transactions on Pattern Analysis and Machine Intelligence
An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Journal of the ACM (JACM)
Experimental evaluation of expert fusion strategies
Pattern Recognition Letters - Special issue on pattern recognition in practice VI
Machine Learning
Introduction to Multiagent Systems
Introduction to Multiagent Systems
Sum Versus Vote Fusion in Multiple Classifier Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
Neural networks: a comprehensive foundation by Simon Haykin, Macmillan, 1994, ISBN 0-02-352781-7.
The Knowledge Engineering Review
The Repeatability of Signatures
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
A Theoretical and Experimental Analysis of Linear Combiners for Multiple Classifier Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Classifier Ensembles with a Random Linear Oracle
IEEE Transactions on Knowledge and Data Engineering
From Template to Image: Reconstructing Fingerprints from Minutiae Points
IEEE Transactions on Pattern Analysis and Machine Intelligence
2D face recognition based on supervised subspace learning from 3D models
Pattern Recognition
An Investigation of Predictive Profiling from Handwritten Signature Data
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
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Designing a biometrics-based system poses many challenges, such as how many and which modalities to use (multimodal configurations being widely adopted), which classification methods are appropriate, user acceptability issues, and so on. Machine learning techniques need as much information as possible to maximise accuracy, but biometric samples are not necessarily straightforward to acquire and usability factors can be very influential. This paper presents a new recognition structure for biometric systems design, using an agent-based approach which maximises the value of the available information. Using handwritten signature as an illustrative modality, we present results which show that carefully structured unimodal systems can deliver excellent performance.