کنفرانس بین المللی کنترل ، ابزار دقیق و اتوماسیون

صفحه اصلی / هشتمین کنفرانس بین المللی کنترل ، ابزار دقیق و اتوماسیون

COVID-19 Detection in Cough Audio Dataset Using Deep Learning Model

نویسندگان :

Marziyeh Sabet¹ Seyedeh Maryam Ghasemi² Amin Ramezani³

1- دانشگاه تربیت مدرس 2- دانشگاه تهران 3- دانشگاه تربیت مدرس

کلمات کلیدی :

CNN, COVID-19, Deep Learning, Cough Sounds

چکیده :

Using Deep Learning methods might be a proper answer to the need of the world for a fast, automatic solution for COVID-19 early-stage diagnosis. In this article, we try to take advantage of Convolutional Neural Network (CNN) systems for this purpose. Our proposed model is based on a CNN network and is trained based on COUGHVID dataset. By implementing feature extraction using MFCC and using data augmentation methods, we tried to develop a fully functional model. The results show that we had improvements compared to other state of the art projects. Based on the metrics we used, we achieved an area under the curve of the receiver operating characteristics of 0.94 on the task of COVID-19 classification.

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یک روش یادگیری عمیق با نظارت مبتنی بر حافظه طولانی کوتاه مدت برای مدلسازی حسگر های نرم

شیدک یزدانی - سید جلیل ساداتی رستمی - سپیده عیسی‌پور

بیشتر

ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 42.2.8