Our participation in the ImageCLEF Wikipedia retrieval task aims to study the efficiency of using two contextual factors in image retrieval: metadata which contains specific infor...
Hatem Awadi, Mouna Torjmen Khemakhem, Maher Ben Je...
Many applications involve multiple-modalities such as text and images that describe the problem of interest. In order to leverage the information present in all the modalities, on...
With the exponential growth of Web 2.0 applications, tags have been used extensively to describe the image contents on the Web. Due to the noisy and sparse nature in the human gene...
The present research scholars are having keen interest in doing their research activities in the area of Data mining all over the world. Especially, [13]Mining Image data is the o...
We present a novel segmentation technique that effectively segments natural images. The method is designed for the purpose of image retrieval and follows the principle of clusterin...
Wojciech Tarnawski, Lukasz Miroslaw, Roman Pawliko...
: Because of the semantic gap between low-level feature and high-level semantic feature of images, the results of the traditional color-based image retrieval can't meet users&...
Active learning is a framework that has attracted a lot of research interest in the content-based image retrieval (CBIR) in recent years. To be effective, an active learning syste...
The ImageCLEF Photo Retrieval Task 2009 focused on image retrieval and diversity. A new collection was utilised in this task consisting of approximately half a million images with...
Monica Lestari Paramita, Mark Sanderson, Paul Clou...
MedGIFT is a medical imaging research group of the Geneva University Hospitals and the University of Geneva, Switzerland. Since 2004, the medGIFT group has participated in the Ima...
Tracking is a major issue of virtual and augmented reality applications. Single object tracking on monocular video streams is fairly well understood. However, when it comes to mul...