Deep Learning and its applications have cascaded impactful research and development
with a diverse range of modalities present in the real-world data. More recently, this has …

The multimodal task of Visual Question Answering (VQA) encompassing elements of
Computer Vision (CV) and Natural Language Processing (NLP), aims to generate answers …

In this paper, we discuss the initial attempts at boosting understanding human language
based on deep-learning models with quantum computing. We successfully train a quantum …

The legal landscape encompasses a wide array of lawsuit types, presenting lawyers with
challenges in delivering timely and accurate information to clients, particularly concerning …

Automatic machine learning-based (ML-based) medical report generation systems for retinal
images suffer from a relative lack of interpretability. Hence, such ML-based systems are still …

Evaluating the quality of automatically generated image descriptions is challenging,
requiring metrics that capture various aspects such as grammaticality, coverage …

When video collections become huge, how to explore both within and across videos
efficiently is challenging. Video summarization is one of the ways to tackle this issue …

In this work, we propose an AI-based method that intends to improve the conventional retinal
disease treatment procedure and help ophthalmologists increase diagnosis efficiency and …

Traditional video summarization methods generate fixed video representations regardless of
user interest. Therefore such methods limit users' expectations in content search and …

The goal of video summarization is to automatically shorten videos such that it conveys the
overall story without losing relevant information. In many application scenarios, improper …