12 citations · 24 across the 5 of their papers we have counts for
5 papers
Audio-Based Deep Learning Frameworks for Detecting COVID-19
Dat Ngo, Lam Pham, Truong Hoang +2
This paper evaluates a wide range of audio-based deep learning frameworks applied to the breathing, cough, and speech sounds for detecting COVID-19. In general, the audio recording…
Sound-Dr: Reliable Sound Dataset and Baseline Artificial Intelligence System for Respiratory Illnesses
Truong V. Hoang, Quang H. Nguyen, Cuong Q. Nguyen +2
As the burden of respiratory diseases continues to fall on society worldwide, this paper proposes a high-quality and reliable dataset of human sounds for studying respiratory illne…
An Audio-Visual Dataset and Deep Learning Frameworks for Crowded Scene Classification
Lam Pham, Dat Ngo, Phu X. Nguyen +2
This paper presents a task of audio-visual scene classification (SC) where input videos are classified into one of five real-life crowded scenes: 'Riot', 'Noise-Street', 'Firework-…
COVID-19 Diagnosis from Cough Acoustics using ConvNets and Data Augmentation
Saranga Kingkor Mahanta, Darsh Kaushik, Shubham Jain +2
With the periodic rise and fall of COVID-19 and countries being inflicted by its waves, an efficient, economic, and effortless diagnosis procedure for the virus has been the utmost…
A Cough-based deep learning framework for detecting COVID-19
Truong Hoang, Lam Pham, Dat Ngo +1
This paper presents a deep learning framework for detecting COVID-19 positive subjects from their cough sounds. In particular, the proposed approach comprises two main steps. In th…