In this paper, we propose a feature weighting method that works in both the input space and the kernel-induced feature space. It assumes only the availability of similarity (dissimilarity) information, and the number of parameters in the transformation does not depend on the number of features. Besides feature weighting, it can also be regarded as performing nonparametric kernel adaptation. Exp...

Convolutional neural networks based single-image superresolution (SISR) has made great progress in recent years. However, it is difficult to apply these methods real-world scenarios due the computational and memory cost. Meanwhile, how take full advantage of intermediate features under constraints limited parameters calculations also a huge challenge. To alleviate issues, we propose lightweight...

Discovering and extracting knowledge from large databases are key elements in granular computing (GrC). The extracted, the form of information granules can be used to build rule-based systems such as Fuzzy Logic inference systems. Algorithms for iterative data granulation literature treat all variables equally neglects difference variable importance, a potential mechanism influence clustering p...