Information fusion in content based image retrieval: A comprehensive overview
An ever increasing part of communication between persons involve the use of pictures, due
to the cheap availability of powerful cameras on smartphones, and the cheap availability of …
to the cheap availability of powerful cameras on smartphones, and the cheap availability of …
Multimodal distributional semantics
Distributional semantic models derive computational representations of word meaning from
the patterns of co-occurrence of words in text. Such models have been a success story of …
the patterns of co-occurrence of words in text. Such models have been a success story of …
A new approach to cross-modal multimedia retrieval
The problem of joint modeling the text and image components of multimedia documents is
studied. The text component is represented as a sample from a hidden topic model, learned …
studied. The text component is represented as a sample from a hidden topic model, learned …
On the role of correlation and abstraction in cross-modal multimedia retrieval
The problem of cross-modal retrieval from multimedia repositories is considered. This
problem addresses the design of retrieval systems that support queries across content …
problem addresses the design of retrieval systems that support queries across content …
Learning cross-media joint representation with sparse and semisupervised regularization
Cross-media retrieval has become a key problem in both research and application, in which
users can search results across all of the media types (text, image, audio, video, and 3-D) by …
users can search results across all of the media types (text, image, audio, video, and 3-D) by …
[PDF][PDF] Multimodal fusion: a review, taxonomy, open challenges, research roadmap and future directions
The present work collects a plethora of previous research work in the field of multimodal
fusion which despite a lot of research could not handle the imperfections. These …
fusion which despite a lot of research could not handle the imperfections. These …
Semi-supervised cross-media feature learning with unified patch graph regularization
With the rapid growth of multimedia data such as text, image, video, audio, and 3-D model,
cross-media retrieval has become increasingly important, because users can retrieve the …
cross-media retrieval has become increasingly important, because users can retrieve the …
Heterogeneous metric learning with joint graph regularization for cross-media retrieval
As the major component of big data, unstructured heterogeneous multimedia content such
as text, image, audio, video and 3D increasing rapidly on the Internet. User demand a new …
as text, image, audio, video and 3D increasing rapidly on the Internet. User demand a new …
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 …
Semantic combination of textual and visual information in multimedia retrieval
The goal of this paper is to introduce a set of techniques we call semantic combination in
order to efficiently fuse text and image retrieval systems in the context of multimedia …
order to efficiently fuse text and image retrieval systems in the context of multimedia …