This paper presents a few-shot personalized saliency prediction using
te...
We present a novel multimodal interpretable VQA model that can answer th...
Background and objective: COVID-19 and its variants have caused signific...
Purpose: Considering several patients screened due to COVID-19 pandemic,...
This paper solves a generalized version of the problem of multi-source m...
Self-supervised learning has developed rapidly and also advances
compute...
Dataset complexity assessment aims to predict classification performance...
Background and objective: Sharing of medical data is required to enable ...
The acquisition of advanced models relies on large datasets in many fiel...
Sharing medical datasets between hospitals is challenging because of the...
Learning concise data representations without supervisory signals is a
f...
This paper proposes a novel self-supervised learning method for learning...
The global outbreak of the Coronavirus 2019 (COVID-19) has overloaded
wo...
We propose a novel self-supervised learning method for medical image
ana...
This paper presents a soft-label anonymous gastric X-ray image distillat...