Results 51 to 60 of about 26,920 (307)
AAU-Net: Attention-Based Asymmetric U-Net for Subject-Sensitive Hashing of Remote Sensing Images
Remote Sensing, 2021 The prerequisite for the use of remote sensing images is that their security must be guaranteed. As a special subset of perceptual hashing, subject-sensitive hashing overcomes the shortcomings of the existing perceptual hashing that cannot distinguish ...
Kaimeng Ding +5 more
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MESH: A Flexible Manifold-Embedded Semantic Hashing for Cross-Modal Retrieval
IEEE Access, 2020 Hashing based methods for cross-modal retrieval has been widely explored in recent years. However, most of them mainly focus on the preservation of neighborhood relationship and label consistency, while ignore the proximity of neighbors and proximity of ...
Fangming Zhong +3 more
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Enhancing deep hashing with graph filters and autoencoder-based embeddings [PDF]
PeerJ Computer ScienceDeep hashing has emerged as an efficient and robust solution for image retrieval through representation learning. However, convolutional neural network (CNN)-based hashing methods are constrained by their reliance on grid structures, limiting their ...
Sooin Kim +5 more
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Deep Hashing Based on Class-Discriminated Neighborhood Embedding
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Deep-hashing methods have drawn significant attention during the past years in the field of remote sensing (RS) owing to their prominent capabilities for capturing the semantics from complex RS scenes and generating the associated hash codes in an end-to-
Jian Kang +4 more
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RelaHash: Deep Hashing With Relative Position
IEEE Access, 2023 Deep hashing has been widely used as a solution to encoding binary hash code for approximating nearest neighbor problem. It has been showing superior performance in terms of its ability to index high-level features by learning compact binary code.
Pham Vu Thai Minh +4 more
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Deep Discrete Hashing with Self-supervised Pairwise Labels
, 2017 Hashing methods have been widely used for applications of large-scale image retrieval and classification. Non-deep hashing methods using handcrafted features have been significantly outperformed by deep hashing methods due to their better feature ...
A Andoni +12 more
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SUBIC: A supervised, structured binary code for image search [PDF]
, 2017 For large-scale visual search, highly compressed yet meaningful representations of images are essential. Structured vector quantizers based on product quantization and its variants are usually employed to achieve such compression while minimizing the ...
Gribonval, Rémi +3 more
core +2 more sources
, 2018 In recent years, hashing methods have been proved to be effective and efficient for the large-scale Web media search. However, the existing general hashing methods have limited discriminative power for describing fine-grained objects that share similar overall appearance but have subtle difference. To solve this problem, we for the first time introduce
Jin, Sheng +5 more
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Enhancing Deep Hashing With GCN-Based Models for Efficient Similarity Search
IEEE AccessDeep hashing models are employed to efficiently store and swiftly search large-scale datasets where data are high dimensional. Their optimization of the loss function and the non-differentiable sign function can lead to inadequate backpropagation ...
Sooin Kim +4 more
doaj +1 more source
Deep Multi-Semantic Fusion-Based Cross-Modal Hashing
Mathematics, 2022 Due to the low costs of its storage and search, the cross-modal retrieval hashing method has received much research interest in the big data era. Due to the application of deep learning, the cross-modal representation capabilities have risen markedly ...
Xinghui Zhu +3 more
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