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 …

In recent years a vast amount of visual content has been generated and shared from many
fields, such as social media platforms, medical imaging, and robotics. This abundance of …

The content based image retrieval aims to find the similar images from a large scale dataset
against a query image. Generally, the similarity between the representative features of the …

With the development of Internet technology and the popularity of digital devices, Content-
Based Image Retrieval (CBIR) has been quickly developed and applied in various fields …

In the study of data-driven prognostic methods of machinery, much attention has been paid
to constructing health indicators (HIs). Most of the existing HIs, however, are manually …

With the availability of internet technology and the low-cost of digital image sensor,
enormous amount of image databases have been created in different kind of applications …

In this paper we propose a model retraining method for learning more efficient convolutional
representations for Content Based Image Retrieval. We employ a deep CNN model to obtain …

In recent years a vast amount of visual content has been generated and shared from various
fields, such as social media platforms, medical images, and robotics. This abundance of …

Automatic detection of casting defects on radiography images is an important technology to
automatize digital radiography defect inspection. Traditionally, in an industrial application …

Low-level features and deep features each have their own advantages and disadvantages
in image representation. However, combining their advantages within a CBIR framework …