Multimedia content analysis is applied in different real‐world computer vision applications,
and digital images constitute a major part of multimedia data. In last few years, the …

We have witnessed great interest and a wealth of promise in content-based image retrieval
as an emerging technology. While the last decade laid foundation to such promise, it also …

The recent development in learning deep representations has demonstrated its wide
applications in traditional vision tasks like classification and detection. However, there has …

This paper investigates the problem of modeling Internet images and associated text or tags
for tasks such as image-to-image search, tag-to-image search, and image-to-tag search …

Clustering is an important topic in machine learning and data mining. Recently, deep
clustering, which learns feature representations for clustering tasks using deep neural …

Image classification has gained lot of attention due to its application in different computer
vision tasks such as remote sensing, scene analysis, surveillance, object detection, and …

Nowadays, more and more images are available. However, to find a required image for an
ordinary user is a challenging task. Large amount of researches on image retrieval have …

The complexity of multimedia contents is significantly increasing in the current digital world.
This yields an exigent demand for developing highly effective retrieval systems to satisfy …

Image auto-annotation is an important open problem in computer vision. For this task we
propose TagProp, a discriminatively trained nearest neighbor model. Tags of test images …

Based on keypoints extracted as salient image patches, an image can be described as a"
bag of visual words" and this representation has been used in scene classification. The …