Despite the progress made in the field of medical imaging, it remains a large area of open
research, especially due to the variety of imaging modalities and disease-specific …

Automatic post-disaster mapping of building damage using remote sensing images is an
important and time-critical element of disaster management. The characteristics of remote …

The unstructured nature of clinical narratives makes them complex for automatically
extracting information. Feature learning is an important precursor to document classification …

With the availability of whole-slide imaging in pathology, high-resolution images offer a more
convenient disease observation but also require content-based retrieval of large scans. The …

A medical annotation system for radiology images extracts clinically useful information from
the images, allowing the machines to infer useful abstract semantics and become capable of …

Automatic image captioning has been studied extensively over the last few years, driven by
breakthroughs in deep learning-based image-to-text translation models. However, most of …

This paper introduces a novel approach to tackle the existing gap on message translations
in dialogue systems. Currently, submitted messages to the dialogue systems are considered …

This paper proposes a new approach of automatic medical image annotation since a social
network whose users are student doctors in radiology in order to obtain report rapids on …

Classification of benign and malignant masses in mammograms is a challenging problem. It
has wide applications in the development of Computer Aided Diagnosis (CAD) systems …

The current availability of large datasets composed of heterogeneous objects stresses the
importance of large-scale clustering of mixed complex items. Several algorithms have been …