Online multi-modal hashing with dynamic query-adaption
Multi-modal hashing is an effective technique to support large-scale multimedia retrieval,
due to its capability of encoding heterogeneous multi-modal features into compact and …
due to its capability of encoding heterogeneous multi-modal features into compact and …
Exploring auxiliary context: discrete semantic transfer hashing for scalable image retrieval
Unsupervised hashing can desirably support scalable content-based image retrieval for its
appealing advantages of semantic label independence, memory, and search efficiency …
appealing advantages of semantic label independence, memory, and search efficiency …
Deep asymmetric pairwise hashing
Recently, deep neural networks based hashing methods have greatly improved the
multimedia retrieval performance by simultaneously learning feature representations and …
multimedia retrieval performance by simultaneously learning feature representations and …
Discrete multimodal hashing with canonical views for robust mobile landmark search
Mobile landmark search (MLS) recently receives increasing attention for its great practical
values. However, it still remains unsolved due to two important challenges. One is high …
values. However, it still remains unsolved due to two important challenges. One is high …
Polycrystalline silicon wafer defect segmentation based on deep convolutional neural networks
Defect segmentation is an important way for defect detection in machine vision. For
polycrystalline silicon wafer production, it is difficult to automatically segment defects due to …
polycrystalline silicon wafer production, it is difficult to automatically segment defects due to …
[BOOK][B] Preference-based spatial co-location pattern mining
L Wang, Y Fang, L Zhou - 2022 - Springer
The development of information technology has enabled many different technologies to
collect large amounts of spatial data every day. It is of very great significance to discover …
collect large amounts of spatial data every day. It is of very great significance to discover …
Adaptive collaborative similarity learning for unsupervised multi-view feature selection
In this paper, we investigate the research problem of unsupervised multi-view feature
selection. Conventional solutions first simply combine multiple pre-constructed view-specific …
selection. Conventional solutions first simply combine multiple pre-constructed view-specific …
Multiple deep neural networks with multiple labels for cross-modal hashing retrieval
Y **e, X Zeng, T Wang, L Xu, D Wang - Engineering Applications of …, 2022 - Elsevier
Most deep hashing methods for cross-modal retrieval use semantic labels to judge simply
whether a pair of data are similar or dissimilar. However, they do not make full use of the …
whether a pair of data are similar or dissimilar. However, they do not make full use of the …
Effective lossless condensed representation and discovery of spatial co-location patterns
A spatial co-location pattern is a set of spatial features frequently co-occuring in nearby
geographic spaces. Similar to closed frequent itemset mining, closed co-location pattern …
geographic spaces. Similar to closed frequent itemset mining, closed co-location pattern …
Exploring consistent preferences: discrete hashing with pair-exemplar for scalable landmark search
Content-based visual landmark search (CBVLS) enjoys great importance in many practical
applications. In this paper, we propose a novel discrete hashing with pair-exemplar (DHPE) …
applications. In this paper, we propose a novel discrete hashing with pair-exemplar (DHPE) …