Robust Deep Learning Framework For Predicting Respiratory Anomalies and Diseases

21 January 2020

Papers citing "Robust Deep Learning Framework For Predicting Respiratory Anomalies and Diseases"

7 / 7 papers shown

Title
Training one model to detect heart and lung sound events from single point auscultations Leander Melms Robert R. Ilesan Ulrich Köhler O. Hildebrandt R. Conradt ... Jürgen R. Schaefer Tobias Müller J. Obergassel Nadine Schlicker M. Hirsch 28 2 0 15 Jan 2023
COVID-19 Detection from Respiratory Sounds with Hierarchical Spectrogram Transformers Idil Aytekin Onat Dalmaz Kaan Gonc H. Ankishan E. Saritas Ulas Bagci H. Celik Tolga Çukur 24 12 0 19 Jul 2022
Audio-Based Deep Learning Frameworks for Detecting COVID-19 Dat Ngo L. D. Pham Hoang Van Truong Ş. Kolozali D. Jarchi 50 4 0 10 Feb 2022
An Ensemble of Deep Learning Frameworks Applied For Predicting Respiratory Anomalies L. D. Pham Dat Ngo T. Hoang Alexander Schindler Ian Mcloughlin 39 5 0 09 Jan 2022
Multimedia Datasets for Anomaly Detection: A Review Pratibha Kumari Anterpreet Kaur Bedi Mukesh Saini 38 9 0 10 Dec 2021
Lung Sound Classification Using Co-tuning and Stochastic Normalization T. Nguyen Franz Pernkopf 19 86 0 04 Aug 2021
Neural Networks for Pulmonary Disease Diagnosis using Auditory and Demographic Information M. Hosseini Haoran Ren Hasib-Al Rashid A. Mazumder Bharat Prakash T. Mohsenin 24 20 0 26 Nov 2020