Over the past decades, medical image analytics was greatly facilitated by the explosion of
digital imaging techniques, where huge amounts of medical images were produced with …

An ever increasing part of communication between persons involve the use of pictures, due
to the cheap availability of powerful cameras on smartphones, and the cheap availability of …

Visual localization tackles the challenge of estimating the camera pose from images by
using correspondence analysis between query images and a map. This task is computation …

Medical image retrieval and classification have been extremely active research topics over
the past 15 years. Within the ImageCLEF benchmark in medical image retrieval and …

Digitizing pathology is a current trend that makes large amounts of visual data available for
automatic analysis. It allows to visualize and interpret pathologic cell and tissue samples in …

Multimodal medical question answering (MMQA) is a vital area bridging healthcare and
Artificial Intelligence (AI). This survey methodically examines the MMQA research published …

We are living in a multilingual world and the diversity in languages which are used to
interact with information access systems has generated a wide variety of challenges to be …

Content-based multimedia retrieval (CBMR) has been an active research domain since the
mid 1990s. In medicine visual retrieval started later and has mostly remained a research …

We present a new pre-training method, Multimodal Inverse Cloze Task, for Knowledge-
based Visual Question Answering about named Entities (KVQAE). KVQAE is a recently …

Multimodal Retrieval is a well-established approach for image retrieval. Usually, images are
accompanied by text caption along with associated documents describing the image …