4 citations · 4 across the 2 of their papers we have counts for
3 papers
Robust COVID-19 Detection from Cough Sounds using Deep Neural Decision Tree and Forest: A Comprehensive Cross-Datasets Evaluation
Rofiqul Islam, Nihad Karim Chowdhury, Muhammad Ashad Kabir
This research presents a robust approach to classifying COVID-19 cough sounds using cutting-edge machine-learning techniques. Leveraging deep neural decision trees and deep neural…
MMTF-DES: A Fusion of Multimodal Transformer Models for Desire, Emotion, and Sentiment Analysis of Social Media Data
Abdul Aziz, Nihad Karim Chowdhury, Muhammad Ashad Kabir +2
Desire is a set of human aspirations and wishes that comprise verbal and cognitive aspects that drive human feelings and behaviors, distinguishing humans from other animals. Unders…
COVIDFakeExplainer: An Explainable Machine Learning based Web Application for Detecting COVID-19 Fake News
Dylan Warman, Muhammad Ashad Kabir
Fake news has emerged as a critical global issue, magnified by the COVID-19 pandemic, underscoring the need for effective preventive tools. Leveraging machine learning, including d…