Nowadays, the use of Convolutional Neural Networks (CNNs) has led to tremendous
achievements in several computer vision challenges. CNN-based image retrieval methods …

Modern medical information retrieval systems are paramount to manage the insurmountable
quantities of clinical data. These systems empower health care experts in the diagnosis of …

Due to recent development in technology, the complexity of multimedia is significantly
increased and the retrieval of similar multimedia content is an open research problem. In the …

The results of a content based image retrieval system can be evaluated by several
performance measures, each one employing different evaluation criteria. Many of the …

Surprising as it may seem, many of the early adopters of the object-oriented paradigm
already face a number of problems typically encountered in large-scale legacy systems …

In the field of image processing, texture features and color are fundamental visual cue with
complementary roles. They are used in many applications and in a large variety of areas …

The main problem in content-based image retrieval (CBIR) systems is the semantic gap
which needs to be reduced for efficient retrieval. The common imaging signs (CISs) which …

This paper contributes a new variant of multi-trend structure descriptor (MTSD) for efficient
content based image retrieval. The proposed variant of MTSD encodes color/edge …

This paper proposes a new method for visual multimedia content encryption using Cellular
Automata (CA). The encryption scheme is based on the application of an attribute of the CLF …

Content-based image retrieval (CBIR) with global features is notoriously noisy, especially for
image queries with low percentages of relevant images in a collection. Moreover, CBIR …