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This paper presents a content-based image retrieval (CBIR) system using multiple Hierarchical Temporal Memory classifiers. in order to improve the efficiency of image management and retrieval, the CBIR system proposed in this paper take advantage of Hierarchical Temporal Memory Algorithm which replicates the structure and function of the human neocortex. in this study, multiple Hierarchical Temporal Memory classifiers were used to provide an intelligent system that aims to understand a query image's category semantics, rather than the low-level image features for image indexing and retrieval. the system supports query by example image, the experiments based on Internet images show the efficiency of our method.