Supervised learning aims to build a function or model that seeks as many mappings as
possible between the training data and outputs, where each training data will predict as a …

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 …

The application of machine learning to radiological images is an increasingly active
research area that is expected to grow in the next five to ten years. Recent advances in …

In recent times, a large number of medical images are generated, due to the evolution of
digital imaging modalities and computer vision application. Due to variation in the shape …

Modeling low level features to high level semantics in medical imaging is an important
aspect in filtering anatomy objects. Bag of Visual Words (BOVW) representations have been …

In medical applications, retrieving similar images from repositories is most essential for
supporting diagnostic imaging-based clinical analysis and decision support systems …

Abstract Content Based Image Retrieval (CBIR) has been widely studied in the last two
decades. Unlike text based image retrieval techniques, visual properties of images are used …

With the advent of large-scale databases in the last two decades, content based image
retrieval (CBIR) has been widely investigated. Studies show that the performance of the …

A huge amount of image data is being collected in real world sectors. Image data analytics
provides information about important facts and issues of a particular domain. But, it is …

Testing is one of the important methodologies used by various countries in order to fight
against COVID-19 infection. The infection is considered as one of the deadliest ones …