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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Within the Lack of Chest COVID-19 X-ray Dataset: A Novel Detection Model Based on GAN and Deep Transfer Learning
Mohamed Loey, Florentín Smarandache, Nour Eldeen M. Khalifa
Symmetry (2020) Vol. 12, Iss. 4, pp. 651-651
Open Access | Times Cited: 513

Showing 1-25 of 513 citing articles:

A hybrid deep transfer learning model with machine learning methods for face mask detection in the era of the COVID-19 pandemic
Mohamed Loey, Gunasekaran Manogaran, Mohamed Hamed N. Taha, et al.
Measurement (2020) Vol. 167, pp. 108288-108288
Open Access | Times Cited: 705
A combined deep CNN-LSTM network for the detection of novel coronavirus (COVID-19) using X-ray images
Md. Zabirul Islam, Md. Milon Islam, Amanullah Asraf
Informatics in Medicine Unlocked (2020) Vol. 20, pp. 100412-100412
Open Access | Times Cited: 550
Multi-task deep learning based CT imaging analysis for COVID-19 pneumonia: Classification and segmentation
Amine Amyar, Romain Modzelewski, Hua Li, et al.
Computers in Biology and Medicine (2020) Vol. 126, pp. 104037-104037
Open Access | Times Cited: 497
Generative adversarial network: An overview of theory and applications
Alankrita Aggarwal, Mamta Mittal, Gopi Battineni
International Journal of Information Management Data Insights (2021) Vol. 1, Iss. 1, pp. 100004-100004
Open Access | Times Cited: 490
Fighting against COVID-19: A novel deep learning model based on YOLO-v2 with ResNet-50 for medical face mask detection
Mohamed Loey, Gunasekaran Manogaran, Mohamed Hamed N. Taha, et al.
Sustainable Cities and Society (2020) Vol. 65, pp. 102600-102600
Open Access | Times Cited: 443
A Decade Survey of Transfer Learning (2010–2020)
Shuteng Niu, Yongxin Liu, Jian Wang, et al.
IEEE Transactions on Artificial Intelligence (2020) Vol. 1, Iss. 2, pp. 151-166
Open Access | Times Cited: 417
Federated Learning for Smart Healthcare: A Survey
Dinh C. Nguyen, Quoc‐Viet Pham, Pubudu N. Pathirana, et al.
ACM Computing Surveys (2022) Vol. 55, Iss. 3, pp. 1-37
Open Access | Times Cited: 360
Covid-19 classification by FGCNet with deep feature fusion from graph convolutional network and convolutional neural network
Shuihua Wang‎, Vishnuvarthanan Govindaraj, J. M. Górriz, et al.
Information Fusion (2020) Vol. 67, pp. 208-229
Open Access | Times Cited: 328
Automated Deep Transfer Learning-Based Approach for Detection of COVID-19 Infection in Chest X-rays
Nripendra Narayan Das, Naresh Kumar, Manjit Kaur, et al.
IRBM (2020) Vol. 43, Iss. 2, pp. 114-119
Open Access | Times Cited: 315
Attention-based VGG-16 model for COVID-19 chest X-ray image classification
Chiranjibi Sitaula, Mohammad Belayet Hossain
Applied Intelligence (2020) Vol. 51, Iss. 5, pp. 2850-2863
Open Access | Times Cited: 282
Deep-chest: Multi-classification deep learning model for diagnosing COVID-19, pneumonia, and lung cancer chest diseases
Dina M. Ibrahim, Nada M. Elshennawy, Amany Sarhan
Computers in Biology and Medicine (2021) Vol. 132, pp. 104348-104348
Open Access | Times Cited: 273
A Review on Deep Learning Techniques for the Diagnosis of Novel Coronavirus (COVID-19)
Md. Milon Islam, Fakhri Karray, Reda Alhajj, et al.
IEEE Access (2021) Vol. 9, pp. 30551-30572
Open Access | Times Cited: 264
Identification of COVID-19 samples from chest X-Ray images using deep learning: A comparison of transfer learning approaches
Md Mamunur Rahaman, Chen Li, Yudong Yao, et al.
Journal of X-Ray Science and Technology (2020) Vol. 28, Iss. 5, pp. 821-839
Open Access | Times Cited: 261
A deep transfer learning model with classical data augmentation and CGAN to detect COVID-19 from chest CT radiography digital images
Mohamed Loey, Gunasekaran Manogaran, Nour Eldeen M. Khalifa
Neural Computing and Applications (2020)
Open Access | Times Cited: 249
A comprehensive survey of recent trends in deep learning for digital images augmentation
Nour Eldeen M. Khalifa, Mohamed Loey, Seyedali Mirjalili
Artificial Intelligence Review (2021) Vol. 55, Iss. 3, pp. 2351-2377
Open Access | Times Cited: 233
COVID-19 classification by CCSHNet with deep fusion using transfer learning and discriminant correlation analysis
Shuihua Wang‎, Deepak Ranjan Nayak, David S. Guttery, et al.
Information Fusion (2020) Vol. 68, pp. 131-148
Open Access | Times Cited: 227
GAN-based anomaly detection: A review
Xuan Xia, Xizhou Pan, Nan Li, et al.
Neurocomputing (2022) Vol. 493, pp. 497-535
Closed Access | Times Cited: 220
Medical image analysis based on deep learning approach
Murali Krishna Puttagunta, S. Ravi
Multimedia Tools and Applications (2021)
Open Access | Times Cited: 198
Applications of artificial intelligence in battling against covid-19: A literature review
Mohammad-H. Tayarani N.
Chaos Solitons & Fractals (2020) Vol. 142, pp. 110338-110338
Open Access | Times Cited: 193
Deploying Machine and Deep Learning Models for Efficient Data-Augmented Detection of COVID-19 Infections
Ahmed Sedik, Abdullah M. Iliyasu, Basma Abd El-Rahiem, et al.
Viruses (2020) Vol. 12, Iss. 7, pp. 769-769
Open Access | Times Cited: 184
ResNet-50 vs VGG-19 vs training from scratch: A comparative analysis of the segmentation and classification of Pneumonia from chest X-ray images
Victor Ikechukwu Agughasi, S. Murali, R Deepu, et al.
Global Transitions Proceedings (2021) Vol. 2, Iss. 2, pp. 375-381
Open Access | Times Cited: 171
COVID-19 Detection from Chest X-ray Images Using Feature Fusion and Deep Learning
Nur-A-Alam Alam, Mominul Ahsan, Md. Abdul Based, et al.
Sensors (2021) Vol. 21, Iss. 4, pp. 1480-1480
Open Access | Times Cited: 165
Blockchain and AI-Based Solutions to Combat Coronavirus (COVID-19)-Like Epidemics: A Survey
Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, et al.
IEEE Access (2021) Vol. 9, pp. 95730-95753
Open Access | Times Cited: 153
EMCNet: Automated COVID-19 diagnosis from X-ray images using convolutional neural network and ensemble of machine learning classifiers
Prottoy Saha, Muhammad Sheikh Sadi, Md. Milon Islam
Informatics in Medicine Unlocked (2020) Vol. 22, pp. 100505-100505
Open Access | Times Cited: 152
Review on COVID‐19 diagnosis models based on machine learning and deep learning approaches
Zaid Abdi Alkareem Alyasseri, Mohammed Azmi Al‐Betar, Iyad Abu Doush, et al.
Expert Systems (2021) Vol. 39, Iss. 3
Open Access | Times Cited: 139
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