Principles of artificial intelligence
Principles of artificial intelligence
Training neural nets through stochastic minimization
Neural Networks
Stochastic minimization with adaptive memory
Journal of Computational and Applied Mathematics
Learning Gender with Support Faces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Choosing Multiple Parameters for Support Vector Machines
Machine Learning
Person Identification Using Multiple Cues
IEEE Transactions on Pattern Analysis and Machine Intelligence
SVM vs Regularized Least Squares Classification
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Training ν-Support Vector Classifiers: Theory and Algorithms
Neural Computation
Comparing support vector machines with Gaussian kernels to radialbasis function classifiers
IEEE Transactions on Signal Processing
Novel Design of Decision-Tree-Based Support Vector Machines Multi-class Classifier
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
So near and yet so far: New insight into properties of some well-known classifier paradigms
Information Sciences: an International Journal
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The paper presents a people identity verification system based on the matching of top view finger snapshots, supplementing purely geometrical finger shape comparison with textural information. Low dimensional feature vectors are used to train binary classifiers based on small Gaussian Basis Functions networks which, in this task, are able to match Support Vector Machines performance while outperforming them in runtime efficiency, thereby exposing a different facet in the comparison which complements available literature reports.