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Supervised hashing with kernels
TLDR
A novel kernel-based supervised hashing model which requires a limited amount of supervised information, i.e., similar and dissimilar data pairs, and a feasible training cost in achieving high quality hashing, and significantly outperforms the state-of-the-arts in searching both metric distance neighbors and semantically similar neighbors is proposed. Expand
Hashing with Graphs
TLDR
This paper proposes a novel graph-based hashing method which automatically discovers the neighborhood structure inherent in the data to learn appropriate compact codes and describes a hierarchical threshold learning procedure in which each eigenfunction yields multiple bits, leading to higher search accuracy. Expand
Semi-Supervised Hashing for Large-Scale Search
TLDR
This work proposes a semi-supervised hashing (SSH) framework that minimizes empirical error over the labeled set and an information theoretic regularizer over both labeled and unlabeled sets and presents three different semi- supervised hashing methods, including orthogonal hashing, nonorthogonal hash, and sequential hashing. Expand
Large-scale visual sentiment ontology and detectors using adjective noun pairs
TLDR
This work presents a method built upon psychological theories and web mining to automatically construct a large-scale Visual Sentiment Ontology (VSO) consisting of more than 3,000 Adjective Noun Pairs (ANP) and proposes SentiBank, a novel visual concept detector library that can be used to detect the presence of 1,200 ANPs in an image. Expand
Image Retrieval: Current Techniques, Promising Directions, and Open Issues
TLDR
The survey includes 100+ papers covering the research aspects of image feature representation and extraction, multidimensional indexing, and system design, three of the fundamental bases of content-based image retrieval. Expand
Temporal Action Localization in Untrimmed Videos via Multi-stage CNNs
TLDR
A novel loss function for the localization network is proposed to explicitly consider temporal overlap and achieve high temporal localization accuracy in untrimmed long videos. Expand
Semi-supervised hashing for scalable image retrieval
TLDR
This work proposes a semi-supervised hashing method that is formulated as minimizing empirical error on the labeled data while maximizing variance and independence of hash bits over the labeled and unlabeled data. Expand
VisualSEEk: a fully automated content-based image query system
TLDR
The VisualSEEk system is novel in that the user forms the queries by diagramming spatial arrangements of color regions by utilizing color information, region sizes and absolute and relative spatial locations. Expand
Large Graph Construction for Scalable Semi-Supervised Learning
TLDR
This paper addresses the scalability issue plaguing graph-based semi-supervised learning via a small number of anchor points which adequately cover the entire point cloud via a unique idea called AnchorGraph which provides nonnegative adjacency matrices to guarantee positive semidefinite graph Laplacians. Expand
Large-scale concept ontology for multimedia
TLDR
The large-scale concept ontology for multimedia (LSCOM) is the first of its kind designed to simultaneously optimize utility to facilitate end-user access, cover a large semantic space, make automated extraction feasible, and increase observability in diverse broadcast news video data sets. Expand
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