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Object recognition by zero-shot learning (ZSL) aims to recognise objects without seeing any visual examples by learning knowledge transfer between seen and unseen object classes. This is typically achieved by exploring a semantic embedding space such as attribute space or semantic word vector space. In such a space, both seen and unseen class labels, as(More)
Outlier detection is of much importance in preprocessing of data collected from complex industry system, for the data has strong nonlinearity and poor stability, involving much noise. Outlier detection based on clustering, rejects abnormal data points which have significant difference from others according to the definition of similarity. Self-organizing(More)
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