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Deep regional detail-aware hashing
Deep hashing has been widely studied in recent years. However, most existing methods learn hash codes from the whole image ignoring the region...
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Probability Ordinal-Preserving Semantic Hashing
Existing semantic hashing methods primarily concentrate on preserving piecewise class information or pairwise correlations in learned binary codes,...
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Unsupervised multi-perspective fusing semantic alignment for cross-modal hashing retrieval
Due to its low computational‘ cost, excellent storage capacity, and efficient retrieval performance, unsupervised deep cross-modal hashing methods...
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Asymmetric similarity-preserving discrete hashing for image retrieval
Hashing methods have been widely studied in the image research community due to their low storage and fast computation. However, generating compact...
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RefinerHash: a new hashing-based re-ranking technique for image retrieval
Re-ranking is a task of refining an initially ranked list of images obtained from an image retrieval technique for a given query image, with the goal...
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Locality sensitive hashing with bit selection
Locality sensitive hashing (LSH), one of the most popular hashing techniques, has attracted considerable attention for nearest neighbor search in the...
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Incremental image retrieval method based on feature perception and deep hashing
How to propose an image retrieval algorithm with adaptable model and wide range of applications for large-scale datasets has become a critical...
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Fast unsupervised consistent and modality-specific hashing for multimedia retrieval
Hashing is an effective technique to solve large-scale data storage problem and achieve efficient retrieval, and it is also a core technology to...
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Robust supervised matrix factorization hashing with application to cross-modal retrieval
In recent years, hashing methods have received extensive attention in multimedia search due to their high computational and storage efficiency....
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Hierarchical modal interaction balance cross-modal hashing for unsupervised image-text retrieval
As multimedia technologies advance, untagged image-text data processing has become central in cross-modal retrieval. However, current methods often...
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An Image Hashing Algorithm Based on a Convolutional Neural Network
AbstractThe purpose is to develop an image hashing algorithm using convolutional neural networks. The proposed algorithm consists of three phases:...
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Modified dual attention triplet-supervised hashing network for image retrieval
In view of the problems of insufficient feature extraction and ineffective capture of correlation between deep features in existing image retrieval...
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Ordinal-Preserving Latent Graph Hashing
Current research on semantic-preserving hashing for similarity search primarily focuses on exploring semantic similarities among pointwise or...
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Quantized hashing: enabling resource-efficient deep learning models at the edge
Edge computing is the best savior for latency-critical applications. It brings processing closer to the end-user and provides a secure platform for...
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C# Hashing and Checksum
In this eighth chapter, we delve into the significance of data integrity in the digital age and explore the robust tools C# provides for ensuring...
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CLIP-based fusion-modal reconstructing hashing for large-scale unsupervised cross-modal retrieval
As multi-modal data proliferates, people are no longer content with a single mode of data retrieval for access to information. Deep hashing retrieval...
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Sparse Graph Hashing with Spectral Regression
Learning-based hashing has received increasing research attention due to its promising efficiency for large-scale similarity search. However, most...
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Image perceptual hashing for content authentication based on Watson’s visual model and LLE
Image perceptual hashing has been widely used in image content authentication. In order to extract hashing sequences that are more consistent with...
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Deep supervised hashing with hard example pairs optimization for image retrieval
Compared with the traditional hashing methods, deep hashing methods generate hash codes with rich semantic information and greatly improve the...
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Weighted Contrastive Hashing
The development of unsupervised hashing is advanced by the recent popular contrastive learning paradigm. However, previous contrastive learning-based...