COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images
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Summary
COVID-Net is introduced, a deep convolutional neural network design tailored for the detection of COVID-19 cases from chest X-ray (CXR) images that is open source and available to the general public, and COVIDx, an open access benchmark dataset comprising of 13,975 CXR images across 13,870 patient patient cases.
- Type
- preprint
- Published
- 2020-03-22
- Cited by
- 2,769
- References
- 81
- Access
- Open access
- OpenAlex
- https://openalex.org/W3012582186
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:215768886
Keywords
Coronavirus disease 2019 (COVID-19), Convolutional neural network, Computer science, Benchmark (surveying), Audit
References
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Cited by
- Comparing different deep learning architectures for classification of chest radiographs
- Can AI Help in Screening Viral and COVID-19 Pneumonia?
- Mapping the Landscape of Artificial Intelligence Applications against COVID-19
- Understanding the COVID19 Outbreak: A Comparative Data Analytics and Study
- COVID-ResNet: A Deep Learning Framework for Screening of COVID19 from Radiographs
- Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation, and Diagnosis for COVID-19
- Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network
- COVID-CAPS: A capsule network-based framework for identification of COVID-19 cases from X-ray images
- AI4COVID-19: AI enabled preliminary diagnosis for COVID-19 from cough samples via an app
- COVID-MobileXpert: On-Device COVID-19 Screening using Snapshots of Chest X-Ray
- COVID_MTNet: COVID-19 Detection with Multi-Task Deep Learning Approaches
- Unveiling COVID-19 from CHEST X-Ray with Deep Learning: A Hurdles Race with Small Data
- Deep Learning on Chest X-ray Images to Detect and Evaluate Pneumonia Cases at the Era of COVID-19
- Multi-task Deep Learning Based CT Imaging Analysis For COVID-19: Classification and Segmentation
- Radiologist-Level COVID-19 Detection Using CT Scans with Detail-Oriented Capsule Networks
- Iteratively Pruned Deep Learning Ensembles for COVID-19 Detection in Chest X-rays
- Accurate Prediction of COVID-19 using Chest X-Ray Images through Deep Feature Learning model with SMOTE and Machine Learning Classifiers
- A modified deep convolutional neural network for detecting COVID-19 and pneumonia from chest X-ray images based on the concatenation of Xception and ResNet50V2
- COVID-19 Control by Computer Vision Approaches: A Survey
- CoroNet: A Deep Network Architecture for Semi-Supervised Task-Based Identification of COVID-19 from Chest X-ray Images
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