In machine learning, two approaches outperform traditional algorithms: ensemble learning
and deep learning. The former refers to methods that integrate multiple base models in the …

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 …

This paper presents a novel image feature representation method, namely color difference
histograms (CDH), for image retrieval. This method is entirely different from the existing …

In content‐based image retrieval (CBIR), primitive image signatures are critical because
they represent the visual characteristics. Image signatures, which are algorithmically …

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

It is a very challenging problem to well simulate visual attention mechanisms for content-
based image retrieval. In this paper, we propose a novel computational visual attention …

Abstract The Local Binary Pattern (LBP) operator and its variants play an important role as
the image feature extractor in the textural image retrieval and classification. The LBP-based …

Image retrieval is one of the hot research topics in computer vision which has been paid
much attention by researchers in the last decade. Image retrieval refers to retrieving more …

With the popularity of multimedia technology, information is always represented from
multiple views. Even though multiview data can reflect the same sample from different …

This paper presents an effective image retrieval method by combining high-level features
from convolutional neural network (CNN) model and low-level features from dot-diffused …