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For large-scale image retrieval, high dimensional features make the retrieval system inefficiency. In this paper, we propose a framework of deep feature hash codes for content-based image retrieval system. In this framework, we firstly extract image features by a pre-trained convolutional neural networks model. Secondly, we use different hashing methods for binary feature extraction. Finally, we use...
For large-scale image retrieval, high-dimensional image representations derived from pre-trained Convolutional Neural Networks (CNNs) make the retrieval system inefficiency. In this paper, we propose to combine nonlinear dimension reduction and hashing method for efficient image retrieval. We firstly extract 4096-dimension features by a pre-trained CNNs model. Secondly, we use t-Distributed Stochastic...
Within software coding standards, identifier naming plays an important role. Identifier naming conventions were divided into four categories in our research - Hungarian, Pascal, Camel and Underscore. Such techniques in compiler theory as regular expression and lexical analysis were used to extract identifiers and to match them with the defined naming conventions in our evaluation system. The consistency...
Demand drives wireless sensor network (WSN) to a promising domain, and interconnecting WSN to current network infrastructure attracts much more attention nowadays. An interconnection method has been proposed, which connected the large-scale WSN to Internet based on IPv6, considering simplicity, flexibility, reliability and low power consumption. In this paper, based on the existing researches, we...
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