A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf
.
Image Retrieval Based on the Weighted and Regional Integration of CNN Features
2022
KSII Transactions on Internet and Information Systems
The features extracted by convolutional neural networks are more descriptive of images than traditional features, and their convolutional layers are more suitable for retrieving images than are fully connected layers. The convolutional layer features will consume considerable time and memory if used directly to match an image. Therefore, this paper proposes a feature weighting and region integration method for convolutional layer features to form global feature vectors and subsequently use them
doi:10.3837/tiis.2022.03.008
fatcat:mwqhxgw4zjgktk52x6rfr34s4y