Deep neural network-based autoencoders can effectively extract high-level abstract features with outstanding generalization performance but suffer from sparsity of extracted features, insufficient robustness, greedy training each layer, and a lack global optimization. In this study, the broad learning system (BLS) is improved to obtain new model for data reconstruction. Support Vector Domain De...

This paper presents a new approach for the automatic generation of fuzzy rule bases for pattern recognition. The general idea of the approach is to use and enhance the fuzzy c-means clustering algorithm. The rule base is generated through an iterative feature clustering approach. The automatic extraction of features is repeated until the generated rule base is giving an unequivocal answer. Alth...

With the proliferation of social images, social image tagging is an essential issue for text-based social image retrieval. However, the original tags annotated by web users are always noisy, irrelevant and incomplete to interpret the image visual contents. In this paper, we propose a nonlinear matrix factorization method with the priors of interand intra-correlations among images and tags to ef...