Handwritten Digit Recognition by a Mixture of Local PrincipalComponent Analysis
Neural Processing Letters
A New Neuro-Fuzzy Classifier with Application to On-Line Face Detection and Recognition
Journal of VLSI Signal Processing Systems
Stochastic Neural Computation II: Soft Competitive Learning
IEEE Transactions on Computers
Face Recognition Using Line Edge Map
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the International Conference, 7th Fuzzy Days on Computational Intelligence, Theory and Applications
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Recent advances in visual and infrared face recognition: a review
Computer Vision and Image Understanding
Facial emotion recognition by adaptive processing of tree structures
Proceedings of the 2006 ACM symposium on Applied computing
Probabilistic based recursive model for adaptive processing of data structures
Expert Systems with Applications: An International Journal
eigenPulse: Robust human identification from cardiovascular function
Pattern Recognition
Designing Model Based Classifiers by Emphasizing Soft Targets
Fundamenta Informaticae - Advances in Artificial Intelligence and Applications
Robust visual similarity retrieval in single model face databases
Pattern Recognition
Using bidimensional regression to assess face similarity
Machine Vision and Applications
Recent advances in subspace analysis for face recognition
SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
Pedestrian detection by multiple decision-based neural networks
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
Designing Model Based Classifiers by Emphasizing Soft Targets
Fundamenta Informaticae - Advances in Artificial Intelligence and Applications
Texture Description Through Histograms of Equivalent Patterns
Journal of Mathematical Imaging and Vision
Optical character recognition: A comprehensive study of hybrid methods
International Journal of Knowledge-based and Intelligent Engineering Systems
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Supervised learning networks based on a decision-based formulation are explored. More specifically, a decision-based neural network (DBNN) is proposed, which combines the perceptron-like learning rule and hierarchical nonlinear network structure. The decision-based mutual training can be applied to both static and temporal pattern recognition problems. For static pattern recognition, two hierarchical structures are proposed: hidden-node and subcluster structures. The relationships between DBNN's and other models (linear perceptron, piecewise-linear perceptron, LVQ, and PNN) are discussed. As to temporal DBNN's, model-based discriminant functions may be chosen to compensate possible temporal variations, such as waveform warping and alignments. Typical examples include DTW distance, prediction error, or likelihood functions. For classification applications, DBNN's are very effective in computation time and performance. This is confirmed by simulations conducted for several applications, including texture classification, OCR, and ECG analysis