Enhancing COVID-19 Diagnosis from Chest X-Ray Images Using Deep Convolutional Neural Networks-Reference-Cited by-同舟云学术

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Enhancing COVID-19 Diagnosis from Chest X-Ray Images Using Deep Convolutional Neural Networks

Published:2023-09-25 Issue: Volume: Page:
ISSN:
Container-title:2023 18th International Workshop on Semantic and Social Media Adaptation & Personalization (SMAP)18th International Workshop on Semantic and Social Media Adaptation & Personalization (SMAP 2023)
language:
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Author:

Kanavos Athanasios¹,Papadimitriou Orestis¹,Maragoudakis Manolis²

Affiliation:

1. University of the Aegean,Department of Information and Communication Systems Engineering,Samos,Greece

2. Ionian University,Department of Informatics,Corfu,Greece

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10255069/10255159/10255200.pdf?arnumber=10255200

Reference30 articles.

1. Modeling Credibility in Social Big Data using LSTM Neural Networks

2. CoroNet: A deep neural network for detection and diagnosis of COVID-19 from chest x-ray images

3. Using Deep Learning Architectures for Detection and Classification of Diabetic Retinopathy

4. COVID-19 detection with X-ray images by using transfer learning

5. Efficient comparison of sentence embeddings

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhancing Disease Diagnosis: A CNN-Based Approach for Automated White Blood Cell Classification;2023 IEEE International Conference on Big Data (BigData);2023-12-15

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