An Investigation of the Effects of Variable Vigilance within the RePART Neuro-Fuzzy Network
Journal of Intelligent and Robotic Systems
RePART: A Modified Fuzzy ARTMAP for Pattern Recognition
Proceedings of the 6th International Conference on Computational Intelligence, Theory and Applications: Fuzzy Days
Laminar cortical dynamics of visual form perception
Neural Networks - 2003 Special issue: Advances in neural networks research IJCNN'03
dFasArt: Dynamic neural processing in FasArt model
Neural Networks
ART-Based Neural Networks for Multi-label Classification
IDA '09 Proceedings of the 8th International Symposium on Intelligent Data Analysis: Advances in Intelligent Data Analysis VIII
Clustering: A neural network approach
Neural Networks
Large-scale neural systems for vision and cognition
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Arabic script language identifications using adaptive neural network
ACST '08 Proceedings of the Fourth IASTED International Conference on Advances in Computer Science and Technology
Brief paper: Applying neuro-fuzzy model dFasArt in control systems
Engineering Applications of Artificial Intelligence
Multi-label classification and extracting predicted class hierarchies
Pattern Recognition
Hierarchical polytope ARTMAP for supervised learning
Journal of Computer Science and Technology
Self-organizing ARTMAP rule discovery
Neural Networks
Online mining dynamic web news patterns using machine learn methods
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
Multilayer Fuzzy ARTMAP: fast learning and fast testing for pattern classification
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Comparison of ARTMAP neural networks for classification for face recognition from video
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
GOFAM: a hybrid neural network classifier combining fuzzy ARTMAP and genetic algorithm
Artificial Intelligence Review
Bayesian ARTMAP for regression
Neural Networks
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A new neural network architecture is introduced for the recognition of pattern classes after supervised and unsupervised learning. Applications include spatio-temporal image understanding and prediction and 3D object recognition from a series of ambiguous 2D views. The architecture, called ART-EMAP, achieves a synthesis of adaptive resonance theory (ART) and spatial and temporal evidence integration for dynamic predictive mapping (EMAP). ART-EMAP extends the capabilities of fuzzy ARTMAP in four incremental stages. Stage 1 introduces distributed pattern representation at a view category field. Stage 2 adds a decision criterion to the mapping between view and object categories, delaying identification of ambiguous objects when faced with a low confidence prediction. Stage 3 augments the system with a field where evidence accumulates in medium-term memory. Stage 4 adds an unsupervised learning process to fine-tune performance after the limited initial period of supervised network training. Each ART-EMAP stage is illustrated with a benchmark simulation example, using both noisy and noise-free data