Integrating outside knowledge for reasoning in visio-linguistic tasks such as visual question
answering (VQA) is an open problem. Given that pretrained language models have been …

The purpose of this paper is to show concisely how we can promote chatbots in the medical
sector and cure infectious diseases. We can create awareness through the users and the …

Abstract Medical VQA (VQA-Med) is a critical multi-modal task that raises attention from the
community. Existing models utilized just one high-level feature map (ie, the last layer feature …

The aim of the image captioning task is to understand various semantic concepts such as
objects and their relationships in an image and combine them to generate a natural …

Exploring the semantic correspondence of image-text pairs is significant as it bridges vision
and language. Most prior works focus on global semantic alignment or local semantic …

In this study, composite materials composed of graphene oxide (GO) synthesized by a
modified Hummers' method and silver nanowires (AgNWs) synthesized by a modified polyol …

To address the issues associated with traditional counter electrodes, a novel gamma-
irradiated chitosan-doped reduced graphene-CuInS2 composite (Chi@ RGO-CIS) was used …

With the remarkable success of the image captioning tasks, visual attention methods have
become a vital part of captioning models. However, most attention-based image captioning …

Understanding different semantic concepts, such as objects and their relationships in an
image, and integrating them to produce a natural language description is the goal of the …

Image captioning is a challenging task that needs the knowledge from both computer vision
algorithms and language processing techniques. The model must be able to understand an …