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• W2085208839 abstract "Content Based Image Retrieval (CBIR) has been one on the most bright research area in the field of computer vision over the last ten years. The bottleneck of current CBIR systems is the semantic gap between low level image features and high level user semantic concepts. In order to overcome this bottleneck, the most of the recent research work in CBIR is focused on reduction of semantic gap. The state of the art techniques available in the literature are divided into three categories: Relevance Feedback Techniques to integrate user's perception, Machine Learning Techniques to associate low level features with high level concepts and Machine Learning using neural network. All above technique requires huge amount of computing power, which may not be available with client machine. This becomes a major challenge for semantic CBIR. In order to overcome this challenge, we propose to use cloud computing as distributed computing environment." @default.
• W2085208839 created "2016-06-24" @default.
• W2085208839 creator A5014389361 @default.
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• W2085208839 date "2013-12-01" @default.
• W2085208839 modified "2023-09-27" @default.
• W2085208839 title "Semantic content based image retrieval technique using cloud computing" @default.
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• W2085208839 doi "https://doi.org/10.1109/iccic.2013.6724277" @default.
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