Computer-aided detection of COVID-19 from X-ray images using multi-CNN and Bayesnet classifier

Deep Residual Learning for Image Recognition

He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474

Very Deep Convolutional Networks for Large-Scale Image Recognition

Simonyan, K., & Zisserman, A. (2014) · arXiv · doi:10.48550/arxiv.1409.1556 · Cited by 114,148

ImageNet: A large-scale hierarchical image database

Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206848 · Cited by 65,333

Densely Connected Convolutional Networks

Huang, G., Liu, Z., Van Der Maaten, L., & Weinberger, K. Q. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.243 · Cited by 48,566

MobileNetV2: Inverted Residuals and Linear Bottlenecks

Sandler, M., Howard, A., Zhu, M., Zhmoginov, A., & Chen, L.-C. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00474 · Cited by 28,755

YOLOv3: An Incremental Improvement

Redmon, J., & Farhadi, A. (2018) · arXiv · doi:10.48550/arxiv.1804.02767 · Cited by 17,141

Proceedings of IEEE Conference on Computer Vision and Pattern Recognition

(1993) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.1993.341010 · Cited by 14,475

A Multi-Modal Distributed Real-Time IoT System for Urban Traffic Control (Invited Paper)

Khanam, Z., Achari, V. P. S., Boukhennoufa, I., et al. (2024) · Durham Research Online (Durham University) · doi:10.4230/oasics.ng-res.2024.2 · Cited by 14,048

ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices

Zhang, X., Zhou, X., Lin, M., & Sun, J. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00716 · Cited by 9,982

Learning Transferable Architectures for Scalable Image Recognition

Zoph, B., Vasudevan, V., Shlens, J., & Le, Q. V. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00907 · Cited by 6,875

Cilt Lezyonlarının Sınıflandırılmasında Derin Öğrenme Tabanlı Bir Yöntem

Göreke, V. (2021) · Türk doğa ve fen dergisi :/Türk doğa ve fen dergisi · doi:10.46810/tdfd.797683 · Cited by 3

Detecting Covid-19 in Chest X-Ray Images With Convolutional Neural Network

Rashid, N. M., Shuib, L. M., Eke, C. I., & Azmi, N. A. (2021) · doi:10.1109/ic2se52832.2021.9791913 · Cited by 3

COVID ‐19: A systematic review of prediction and classification techniques

Varma, O. R., Kalra, M., & Kirmani, S. (2023) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.22905 · Cited by 3

DeepCSFusion: Deep Compressive Sensing Fusion for Efficient COVID-19 Classification

Ragab, D. A., Fayed, S. F., & Ghatwary, N. (2024) · Journal of Imaging Informatics in Medicine · doi:10.1007/s10278-024-01011-2 · Cited by 3

A graph-optimized deep learning framework for recognition of Barrett’s esophagus and reflux esophagitis

Hou, M., Wang, J., Liu, T., Li, Z., Hounye, A. H., Liu, X., Wang, K., & Chen, S. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-18910-9 · Cited by 3

Preliminary Classification of Selected Farmland Habitats in Ireland Using Deep Neural Networks

Abraham, L., Davy, S., Zawish, M., Mhapsekar, R. U., Finn, J. A., & Moran, P. (2022) · Sensors · doi:10.3390/s22062190 · Cited by 4

A Deep Learning Framework for the Classification of Lung Diseases Using Chest X-Ray Images

Vyshnavi, M., Abraham, B., & Ramachandran, S. (2022) · Communications in computer and information science · doi:10.1007/978-3-031-11346-8_29 · Cited by 3

AUTOMATED SEGMENTATION OF COVID-19 REGIONS FROM LUNG CT IMAGES USING WATERSHED ALGORITHM AND CLASSIFICATION USING MACHINE LEARNING CLASSIFIERS

Guhan, B., Sowmiya, S., Shivani, B., Umapathy, S., & Rajalakshmi, T. (2021) · Biomedical Engineering Applications Basis and Communications · doi:10.4015/s1016237222500028 · Cited by 3

CovidMulti-Net: A Parallel-Dilated Multi Scale Feature Fusion Architecture for the Identification of COVID-19 Cases from Chest X-ray ImagesPreprint

Khan, M. S. I., Rahman, A., Karim, M. R., Bithi, N. I., Band, S. S., Dehzangi, A., & Alinejad-Rokny, H. (2021) · medRxiv · doi:10.1101/2021.05.19.21257430 · Cited by 3

Deep Ensemble Approaches for Classification of COVID-19 in Chest X-Ray Images

Thomas, J. B., Devvarma, M., & Shihabudheen, K. V. (2021) · International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT) · doi:10.1109/3ict53449.2021.9581389 · Cited by 2

Fuzzy Divergence for Lung Radiography Image Enhancement

Sousa, W. P., Cruz, C. C. P., & Lanzillotti, R. S. (2023) · Trends in Computational and Applied Mathematics · doi:10.5540/tcam.2023.024.04.00699 · Cited by 2

GA-NN and PSO-NN for Medical Images Classification: A Comparative Analysis

Ibrahim, H. K., Rokbani, N., Wali, A., & Alimi, A. M. (2023) · IEEE International Conference on Artificial Intelligence & Green Energy (ICAIGE) · doi:10.1109/icaige58321.2023.10346503 · Cited by 2

CNN Models Using Chest X-Ray Images for COVID-19 Detection: A Survey

Mellal, N., & Zaidi, S. (2023) · Revue d intelligence artificielle · doi:10.18280/ria.370621 · Cited by 2

A Design Using the IoT to Prevent Future Pandemics and Identify People with COVID-19 Symptoms

Sathishkumar, L., Pandala, M. L., Azath, H., Eswaran, M., Pandimurugan, V., Mandviya, R., & Ramakrishna, V. (2022) · International Conference on Advanced Computing and Communication Systems (ICACCS) · doi:10.1109/icaccs54159.2022.9785347 · Cited by 2

Segmentation and classification of brain tumor images using statistical feature extraction and deep neural networks

Joshi, G., Kumar, R., & Chauhan, A. K. S. (2021) · International Journal of Advanced Technology and Engineering Exploration · doi:10.19101/ijatee.2021.874608 · Cited by 2

Performance Comparison of Different Convolutional Neural Network Models for the Detection of COVID-19

Kogilavani, S. V., Sandhiya, R., & Malliga, S. (2022) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-981-19-2948-9_40 · Cited by 2

Application of Advanced Hybrid Models to Identify the Sustainable Financial Management Clients of Long-Term Care Insurance Policy

Chen, Y., Lin, C.-K., Chou, J. C.-L., Chen, S., & Ting, M.-H. (2022) · Sustainability · doi:10.3390/su141912485 · Cited by 2

Android App based on CNN for Covid-19 Detection using Chest X-ray Images

Mellal, N., Bouzekri, K., Sabri, M., & Abdennebi, S. (2022) · International Conference on Pattern Analysis and Intelligent Systems (PAIS) · doi:10.1109/pais56586.2022.9946916 · Cited by 2

Modular Approach for Neural Networks in Medical Image Classification with Enhanced Fuzzy Integration

Varela-Santos, S., & Melín, P. (2022) · Studies in computational intelligence · doi:10.1007/978-3-031-08266-5_2 · Cited by 1

PDCapsNet: A Convolution Neural Network Method for COVID-19 Detection from Chest X-Ray Images

Liang, Z., Lu, H., You, C., Zhu, W., Xie, L. H., & Yao, Y. (2023) · International Conference on Information Technology in Medicine and Education · doi:10.1109/itme60234.2023.00058 · Cited by 1

A Deep Learning Framework for COVID-19 Diagnosis from Computed Tomography

Mansouri, N., Sultan, K., Ahmad, A., Alseadoon, I. M., & Alkhalil, A. (2022) · Intelligent Automation & Soft Computing · doi:10.32604/iasc.2022.025046 · Cited by 1

Performance Evaluation of CNN-based Transfer Learning for COVID-19 Pneumonia Identification with Various Levels of Layer Partial Freezing

Alissa, K., Obeidat, R., Alqudah, S. F., Obeidat, R., & Ismail, Q. (2022) · International Conference on Engineering & MIS (ICEMIS) · doi:10.1109/icemis56295.2022.9914248 · Cited by 1

Improved Qubit Neural Network Based Computer Aided Detection Model for COVID-19 on Chest Radiographs

Kurdi, W. H. M., Almoussawi, Z. A., Khaleel, B. M., Abdulhussain, Z. N., Al-Attabi, K., & Khalid, R. (2023) · International Conference on Engineering Technology and its Applications (IICETA) · doi:10.1109/iiceta57613.2023.10351200 · Cited by 1

Exploring the Efficacy of Deep CNN Algorithms for Pulmonary Infections Detection using X-rays: Case Study COVID-19

Kalakech, A., & Ibrahim, T. K. (2023) · IEEE International Multidisciplinary Conference on Engineering Technology (IMCET) · doi:10.1109/imcet59736.2023.10368255 · Cited by 1

Classification and Identification of Infectious COVID-19 Virus Using Deep Learning and Machine Learning Techniques: A Comprehensive Analysis

Patnaik, V., Subudhi, A. K., & Mohanty, M. (2024) · SN Computer Science · doi:10.1007/s42979-023-02467-9 · Cited by 1

FiltDeepNet: Architecture for COVID Detection based on Chest X-Ray Images

Selvi, S. S., Agarwal, N., Barkur, P., Mishra, Y., & Kumar, A. (2024) · Signals and communication technology · doi:10.1007/978-3-031-47942-7_34 · Cited by 1

Hybrid PSO-Naive Bayes Algorithm Based COVID-19 Prediction Model

Abu-Samaha, A. M., & Yousef, M. (2024) · International Conference on Cyber Resilience (ICCR) · doi:10.1109/iccr61006.2024.10532987 · Cited by 1

Tongue Image Analysis Using CNN Method to Identify Health Disorders

Nugroho, B., Puspaningrum, E. Y., Via, Y. V., Maulana, H., K., D., Mandyartha, E. P., & Akbar, F. A. (2025) · Nusantara Science and Technology Proceedings · doi:10.11594/nstp.2025.4743 · Cited by 1

The Classification of Covid-19 cases through the Employment of Transfer Learning on X-ray images

Hakimi, N. A., Razman, M. A. M., & Majeed, A. P. P. A. (2021) · Mekatronika · doi:10.15282/mekatronika.v3i1.7151 · Cited by 1

Classification of COVID-19 Cases from X-Ray Images Based on a Modified VGG-16 Model

Kareem, O. S., & Al-Sulaifanie, A. K. (2022) · Traitement du signal · doi:10.18280/ts.390126 · Cited by 1

Analysis of Fifteen Approaches to Automated COVID-19 Detection Using Radiography Images

Soni, K., Kirtivasan, A., Ranjan, R., & Goyal, S. R. (2022) · Lecture notes in electrical engineering · doi:10.1007/978-981-19-0840-8_2 · Cited by 1

Deep convolution classification model-based COVID-19 chest CT image classification

Sujatha, R., & Chatterjee, J. M. (2023) · Elsevier eBooks · doi:10.1016/b978-0-443-19413-9.00022-9 · Cited by 1

MobileCaps: A Lightweight Model for Screening and Severity Analysis of COVID-19 Chest X-Ray ImagesPreprint

Pawan, S. J., Sankar, R., Prabhudev, A. M., Mahesh, P. A., Prakashini, K., Das, S. K., & Rajan, J. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2108.08775 · Cited by 3

COVID-19 Detection using Image Modality: A Review

Kukreja, P., & Gupta, D. (2021) · International Conference on Secure Cyber Computing and Communications (ICSCCC) · doi:10.1109/icsccc51823.2021.9478135

Peer Review #3 of "COVID-Nets: deep CNN architectures for detecting COVID-19 using chest CT scans (v0.2)"

(2021) · PeerJ Computer Science · doi:10.7287/peerj-cs.655v0.2/reviews/3

Peer Review #3 of "COVID-Nets: deep CNN architectures for detecting COVID-19 using chest CT scans (v0.1)"

(2021) · PeerJ Computer Science · doi:10.7287/peerj-cs.655v0.1/reviews/3

Peer Review #1 of "COVID-Nets: deep CNN architectures for detecting COVID-19 using chest CT scans (v0.3)"

(2021) · PeerJ Computer Science · doi:10.7287/peerj-cs.655v0.3/reviews/1

Peer Review #1 of "COVID-Nets: deep CNN architectures for detecting COVID-19 using chest CT scans (v0.2)"

(2021) · PeerJ Computer Science · doi:10.7287/peerj-cs.655v0.2/reviews/1

Peer Review #1 of "COVID-Nets: deep CNN architectures for detecting COVID-19 using chest CT scans (v0.1)"

(2021) · PeerJ Computer Science · doi:10.7287/peerj-cs.655v0.1/reviews/1

Deep Learning Models Evolution Applied to Biomedical Engineering

Garza-Ulloa, J. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-820718-5.00012-x

Parameter Optimization for CNN-LSTM by Using Uniform Experimental Design

Yen, C.-H., Chou, F.-I., Liao, Y., Yang, P.-Y., & Chou, J. (2021) · International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) · doi:10.1109/ispacs51563.2021.9651087

Peer Review #2 of "COVID-Nets: deep CNN architectures for detecting COVID-19 using chest CT scans (v0.1)"

(2021) · PeerJ Computer Science · doi:10.7287/peerj-cs.655v0.1/reviews/2

Peer Review #2 of "COVID-Nets: deep CNN architectures for detecting COVID-19 using chest CT scans (v0.2)"

(2021) · PeerJ Computer Science · doi:10.7287/peerj-cs.655v0.2/reviews/2

Detection of COVID-19 from X-Ray Images. (c2021)

Kandalaft, J. (2021) · doi:10.26756/th.2022.247

Detection of COVID-19 from X-Ray Images: A Novel Three-Phase Approach Combining an Ensemble of Customized Convolutional Neural Networks with Feature Extraction and FusionPreprint

Kandalaft, J., Germanos, M., & Azar, D. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4088408

Analysis Of Covid-19 Using Chest X-Ray Images: An AI Based Prospective

Kohli, H., & Bansal, A. (2022) · International Conference on Computation, Automation and Knowledge Management (ICCAKM) · doi:10.1109/iccakm54721.2022.9990290

Covid-19 Detection Using CNN Model with CT Scan Images

Akhilesh, G. L. S., Lokesh, K., Teja, D. V. P. M., Sai, P. J., Tumuluru, P., & Raju, S. H. (2023) · International Conference on Computer Communication and Informatics (ICCCI) · doi:10.1109/iccci56745.2023.10128444

Randomized Ensemble Approach with ID3 Algorithm For the Prediction datasets with Imbalance Problem

Sasirekha, R., & Kanisha, B. (2023) · International Journal on Recent and Innovation Trends in Computing and Communication · doi:10.17762/ijritcc.v11i4.6447

Rapid and Precise Identification of COVID-19 through Segmentation and Classification of CT and X-ray Images

Saygılı, A. (2023) · Sakarya University Journal of Computer and Information Sciences · doi:10.35377/saucis...1309970

Deep learning for COVID-19 by X-ray images Analysis and Designing Diagnostic Application

Khaleel, T., & Kalakech, A. (2023) · Tikrit Journal of Pure Science · doi:10.25130/tjps.v28i4.1398

An Adaptive Grid Search Based Efficient Ensemble Model for Covid-19 Classification in Chest X-Ray Scans

Naresh, P. V., & Visalakshi, R. (2023) · International Journal of Electrical and Electronics Research · doi:10.37391/ijeer.110324

Efficient Detection of Covid-19 from Chest X-ray Images using CNN Feature Extraction and an Ensemble of Machine Learning Classifiers

Rani, D. L. A., Anishiya, P., & Perumal, T. P. (2023) · Indian Journal of Science and Technology · doi:10.17485/ijst/v16i38.1888

Analysing the changes in texture of lung in CT images due to COVID-19 using local directional texture pattern in comparison with local directional number pattern

Jhansi, B., & Ramesh, M. (2023) · AIP conference proceedings · doi:10.1063/5.0179105

COVID-19 (COV-19) Spreading Diagnoses by Feature Representation Method Through Visual Learning (FVisL-CoV19)

Kakulapati, V., & Jayanthiladevi, A. (2023) · Lecture notes in electrical engineering · doi:10.1007/978-981-99-5997-6_21

Automated Ensemble Deep Learning for Chest X-Ray Covid-19 Image Classification Using Multiple Hyperparameter Optimizations

Mudaser, M., Krathu, W., & Jaiyen, S. (2023) · International Computer Science and Engineering Conference · doi:10.1109/icsec59635.2023.10329679

The Effect of Basic Fusion Techniques in Deep Ensemble Learning-Based Models For Covid-19 Diagnosis

Daşdemir, Y., & ARDUÇ, H. (2023) · Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi · doi:10.47495/okufbed.1220413

Performance of Optimization Techniques in the Deep Learning Approach for Classification of Covid-19 Pneumonia

Nugroho, B. S., & Yuniarti, A. (2023) · IEEE Information Technology International Seminar (ITIS) · doi:10.1109/itis59651.2023.10420082

MobileNet Classifier for Detecting Chest X-Ray Images of COVID-19 based on Convolutional Neural Network

Ghani, S. A. D., Intan, I., & Rizal, M. (2023) · ILKOM Jurnal Ilmiah · doi:10.33096/ilkom.v15i3.1780.488-497

Analysis of Computational Intelligence Techniques for COVID-19 Prediction

Kalra, V., Khanna, M., Bansal, A., Sharma, U., Ahuja, P., Gupta, O. P., & Tuli, S. (2023) · International Conference on Advances in Computation, Communication and Information Technology (ICAICCIT) · doi:10.1109/icaiccit60255.2023.10465833

Sustainable Artificial Intelligence: Assessing Performance in Detecting Fake Images

Alrusaini, O. A. (2024) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2024.0150493

DETECTION AND CLASSIFICATION OF COVID-19 USING GRAY-LEVEL FEATURES AND ENSEMBLE CLASSIFIER

Patnaik, V., Mohanty, M., & Subudhi, A. K. (2024) · Biomedical Engineering Applications Basis and Communications · doi:10.4015/s101623722450025x

Empowering Diagnosis: A Review On Deep Learning Applications for COVID-19 and Pneumonia in X-Ray Images

Yaqoub, K. Y., & Abdulazeez, A. M. (2024) · JISA(Jurnal Informatika dan Sains) · doi:10.31326/jisa.v7i1.2024

Identification and classification of SARS-CoV-2 on chest CT-scan image using GLCM-based feature extraction with K-NN and naïve bayes methods

Rachman, R. R., Dewang, S., Ilyas, S. D. A., & Juarlin, E. (2024) · AIP conference proceedings · doi:10.1063/5.0171488

Detection of COVID-19 from CT Scan Images Using Convolution Neural Network

Aruna, S., Maheswari, M., Saranya, A., Pandey, S., & Gupta, M. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-68908-6_18

Automatic Detection of COVID-19 in Chest X-ray Based on VIT

Khate, K., & Neelima, A. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-82603-0_2

AACNet: attention aided CNN-autoencoder network for precise categorization of respiratory conditions from HRCT scans

Kakati, A., Bhattacharjya, U., Medhi, J. P., & Sarma, K. K. (2025) · Network Modeling Analysis in Health Informatics and Bioinformatics · doi:10.1007/s13721-025-00549-7

CTAN: CNN-Transformer Hybrid Network with Dual-Pathway Attention for Gastric Intestinal Metaplasia Severity Grading

Xue, Y., Xu, R., & Zheng, X. (2025) · International Conference on New Trends in Computational Intelligence (NTCI) · doi:10.1109/ntci67886.2025.11308165

COVID-MRSNet: A Novel Deep Convolutional Neural Network Architecture for Automatic Classification of Coronavirus (SARS-CoV-2), Pneumonia and Healthy Lungs from CXR Images

Ouchicha, C. (2026) · WSEAS Transactions on Circuits and Systems archive · doi:10.37394/23201.2026.25.7

Detection of COVID19 from X-ray images using multiscale Deep Convolutional Neural Network

Muralidharan, N., Gupta, S., Prusty, M. R., & Tripathy, R. K. (2022) · Applied Soft Computing · doi:10.1016/j.asoc.2022.108610 · Cited by 42

Improved convolution neural network for detecting Covid-19 from X-ray images

Kota, S., Reddy, A., Desai, Y. K., & Rachapudi, V. (2020) · European Journal of Molecular & Clinical Medicine

X-ray and CT-scan-based automated detection and classification of covid-19 using convolutional neural networks (CNN)

Thakur, S., & Kumar, A. (2021) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2021.102920 · Cited by 123

Automatic Detection of Covid-19 from Chest X-ray Images using Corona Net

D. L. Asha Rani, P. A. (2023) · Proceeding International Conference on Science and Engineering · doi:10.52783/cienceng.v11i1.324 · Cited by 1

Enhanced COVID-19 Detection from X-ray Images with Convolutional Neural Network and Transfer Learning

Baker, Q. B., Hammad, M., AL-Smadi, M., Al-Jarrah, H., Al-Hamouri, R., & Al-Zboon, S. A. (2024) · Journal of Imaging · doi:10.3390/jimaging10100250 · Cited by 20