Robust modular ARTMAP for multi-class shape recognition

— This paper presents a Fuzzy ARTMAP (FAM) based modular architecture for multi-class pattern recognition known as Modular Adaptive Resonance Theory Map (MARTMAP). The prediction of class membership is made collectively by combining outputs from multiple novelty detectors. Distance-based familiarity discrimination is introduced to improve the robustness of MARTMAP in the presence of noise. The effectiveness of the proposed architecture is analyzed and compared with ARTMAP-FD network, FAM network, and One-Against-One Support Vector Machine (OAO-SVM). Experimental results show that MARTMAP is able to retain effective familiarity discrimination in noisy environment, and yet less sensitive to class imbalance problem as compared to its counterparts.

• Type: Conference
• Year: 2008
• Where: IJCNN
• Authors: Chue Poh Tan, Chen Change Loy, Weng-Kin Lai, Chee Peng Lim
• Keywords: Artificial Intelligence, Distance-based Familiarity Discrimination, Familiarity Discrimination, IJCNN 2008, Modular Adaptive Resonance