Scalable deep hashing for large-scale social image retrieval
Recent years have witnessed the wide application of hashing for large-scale image retrieval,
because of its high computation efficiency and low storage cost. Particularly, benefiting from …
because of its high computation efficiency and low storage cost. Particularly, benefiting from …
Tensor canonical correlation analysis for multi-view dimension reduction
Canonical correlation analysis (CCA) has proven an effective tool for two-view dimension
reduction due to its profound theoretical foundation and success in practical applications. In …
reduction due to its profound theoretical foundation and success in practical applications. In …
Scalable semi-supervised learning by efficient anchor graph regularization
Many graph-based semi-supervised learning methods for large datasets have been
proposed to cope with the rapidly increasing size of data, such as Anchor Graph …
proposed to cope with the rapidly increasing size of data, such as Anchor Graph …
Unsupervised visual hashing with semantic assistant for content-based image retrieval
As an emerging technology to support scalable content-based image retrieval (CBIR),
hashing has recently received great attention and became a very active research domain. In …
hashing has recently received great attention and became a very active research domain. In …
Learning on big graph: Label inference and regularization with anchor hierarchy
Several models have been proposed to cope with the rapidly increasing size of data, such
as Anchor Graph Regularization (AGR). The AGR approach significantly accelerates graph …
as Anchor Graph Regularization (AGR). The AGR approach significantly accelerates graph …
An effective content-based image retrieval technique for image visuals representation based on the bag-of-visual-words model
For the last three decades, content-based image retrieval (CBIR) has been an active
research area, representing a viable solution for retrieving similar images from an image …
research area, representing a viable solution for retrieving similar images from an image …
Social anchor-unit graph regularized tensor completion for large-scale image retagging
Image retagging aims to improve the tag quality of social images by completing the missing
tags, rectifying the noise-corrupted tags, and assigning new high-quality tags. Recent …
tags, rectifying the noise-corrupted tags, and assigning new high-quality tags. Recent …
Convolutional neural networks for relevance feedback in content based image retrieval: A Content based image retrieval system that exploits convolutional neural …
Given the great success of Convolutional Neural Network (CNN) for image representation
and classification tasks, we argue that Content-Based Image Retrieval (CBIR) systems could …
and classification tasks, we argue that Content-Based Image Retrieval (CBIR) systems could …
[图书][B] Content-based image retrieval
V Tyagi - 2017 - Springer
Content-based image retrieval (CBIR), which is aimed to search images from a large size
image database based on visual contents of images in an efficient and accurate way as per …
image database based on visual contents of images in an efficient and accurate way as per …
Content-based image retrieval techniques: a review
V Tyagi, V Tyagi - Content-Based Image Retrieval: Ideas, Influences, and …, 2017 - Springer
In recent years, a rapid increase in the size of digital image databases has been observed.
Everyday gigabytes of images are generated. Consequently, the search for the relevant …
Everyday gigabytes of images are generated. Consequently, the search for the relevant …