(function(doc, html, url) { var widget = doc.createElement("div"); widget.innerHTML = html; var script = doc.currentScript; // e = a.currentScript; if (!script) { var scripts = doc.scripts; for (var i = 0; i < scripts.length; ++i) { script = scripts[i]; if (script.src && script.src.indexOf(url) != -1) break; } } script.parentElement.replaceChild(widget, script); }(document, '

A comprehensive interpretation for Medical Visual Question Answering System

What is it about?

This paper deals with following components, (i). Analyzing and understanding different Medical Visual Question Answering (MVQA) datasets, (ii). Categorize the MVQA techniques based on its uniqueness (iii). The process w.r.t to the proposed MVQA system are discussed in terms of algorithms and system design (iv). Challenges w.r.t to the datasets, techniques, performance metrics are discussed along with its solutions.

Why is it important?

1. Interpretation from dataset 2. Challenges in terms of dataset, performance metrics, techniques are discussed 3. The improvisation of VQA-MED 2019, 2020 and 2021 datasets is used 4. The each step in the proposed MVQA system is explained with the help of algorithms

Read more on Kudos…
The following have contributed to this page:
Sheerin Sitara Noor Mohamed
' ,"url"));