Yuhua Li1, Zhiqiang He1,2, Junxia Ma1,*, Zhifeng Zhang1,*, Wangwei Zhang1, Prasenjit Chatterjee3, Dragan Pamucar4
CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 239-262, 2022, DOI:10.32604/cmes.2022.016287
Abstract The current deep convolution features based on retrieval methods cannot fully use the characteristics of the salient image regions. Also, they cannot effectively suppress the background noises, so it is a challenging task to retrieve objects in cluttered scenarios. To solve the problem, we propose a new image retrieval method that employs a novel feature aggregation approach with an attention mechanism and utilizes a combination of local and global features. The method first extracts global and local features of the input image and then selects keypoints from local features by using the attention mechanism. After that, the feature aggregation mechanism… More >
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