This work combines semantic reasoning and machine learning to create tools that allow
curators of the visual art collections to identify and correct the annotations of the artwork as …

Object detection in remotely sensed (RS) satellite imagery has gained significance in smart
city concepts, which include urban planning, disaster management, and environmental …

Most existing approaches to image classification neglect the concept of semantics, resulting
in two major shortcomings. Firstly, categories are treated as independent even when they …

This paper uses Mixed Reality (MR) technologies to provide a seamless integration of digital
information in physical environments through human-made annotations. Creating digital …

In object detection, spatial knowledge assisted systems are effective. Object detection is a
main and challenging issue to analyze object-related information. Several existing object …

Several approaches have been proposed in the area of Automatic Image Annotation (AIA) in
order to exploit the relationships between words that are extracted from image categories …

Image retrieval holds significant importance within the realm of computer vision. This paper
introduces SCDNet, a novel network model, leveraging selected feature aggregation for …

This work combines semantic reasoning and machine learning to create tools that allow
curators of the visual art collections to identify and correct the annotations of the artwork as …

Semantic extraction for images is an urgent problem and is applied in many different
semantic retrieval systems. In this paper, a semantic-based image retrieval (SBIR) system is …

The human visual system (HVS) can effectively recognize objects in complex natural scenes
with high speed and accuracy. Many models have been proposed based on HVS among …