Modified AlexNet Convolution Neural Network For Covid-19 Detection Using Chest X-ray Images
First outbreak of COVID-19 was in the city of Wuhan in China in Dec.2019 and then it becomes a pandemic disease all around the world. World Health Organization (WHO) confirmed more than 5.5 million cases and 341,155 deaths from the disease till the time of writing this paper. This new worldwide dise...
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| Format: | Article |
| Language: | English |
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Sulaimani Polytechnic University
2020-06-01
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| Series: | Kurdistan Journal of Applied Research |
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| Online Access: | https://kjar.spu.edu.iq/index.php/kjar/article/view/523 |
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| author | Shadman Q. Salih Hawre Kh. Abdulla Zanear Sh. Ahmed Nigar M. Shafiq Surameery Rasper Dh. Rashid |
| author_facet | Shadman Q. Salih Hawre Kh. Abdulla Zanear Sh. Ahmed Nigar M. Shafiq Surameery Rasper Dh. Rashid |
| author_sort | Shadman Q. Salih |
| collection | DOAJ |
| description | First outbreak of COVID-19 was in the city of Wuhan in China in Dec.2019 and then it becomes a pandemic disease all around the world. World Health Organization (WHO) confirmed more than 5.5 million cases and 341,155 deaths from the disease till the time of writing this paper. This new worldwide disease forced researchers to make more precise way to diagnose COVID-19. In the last decade, medical imaging techniques show its efficiency in helping radiologists to detect and diagnose the diseases. Deep learning and transfer learning algorithms are good techniques to detect disease from different image source types such as X-Ray and CT scan images. In this work we used a deep learning technique based on Convolution Neural Network (CNN) to detect and diagnose COVID-19 disease using Chest X-ray images. Moreover, the modified AlexNet architecture is proposed in different scenarios were differing from each other in terms of the type of the pooling layers and/or the number of the neurons that have used in the second fully connected layer. The used chest X-ray images are gathered from two COVID-19 X-ray image datasets and one dataset includes large number of normal and pneumonia X-ray images. With the proposed models we obtained the same or even better result than the original AlexNet with having a smaller number of neurons in the second fully connected layer.
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| format | Article |
| id | doaj-art-cd6db3b3c503482790a971b782c706aa |
| institution | Kabale University |
| issn | 2411-7684 2411-7706 |
| language | English |
| publishDate | 2020-06-01 |
| publisher | Sulaimani Polytechnic University |
| record_format | Article |
| series | Kurdistan Journal of Applied Research |
| spelling | doaj-art-cd6db3b3c503482790a971b782c706aa2025-02-09T21:00:11ZengSulaimani Polytechnic UniversityKurdistan Journal of Applied Research2411-76842411-77062020-06-015310.24017/covid.14Modified AlexNet Convolution Neural Network For Covid-19 Detection Using Chest X-ray ImagesShadman Q. Salih0Hawre Kh. Abdulla1Zanear Sh. Ahmed2Nigar M. Shafiq Surameery3Rasper Dh. Rashid4Database Technology Department, Technical College of Informatics, Sulaimani Polytechnic University, Sulaimani, IraqDatabase Technology Department, Technical College of Informatics, Sulaimani Polytechnic University, Sulaimani, IraqInformation Technology Department, Erbil Technical institute, Erbil Polytechnic University, Erbil, IraqBuilding and Construction Engineering Department, College of Engineering, University of Garmian Kalar, Sulaimani, IraqSoftware Engineering Department, Faculty of Engineering, Koya University, Koya, Erbil, IraqFirst outbreak of COVID-19 was in the city of Wuhan in China in Dec.2019 and then it becomes a pandemic disease all around the world. World Health Organization (WHO) confirmed more than 5.5 million cases and 341,155 deaths from the disease till the time of writing this paper. This new worldwide disease forced researchers to make more precise way to diagnose COVID-19. In the last decade, medical imaging techniques show its efficiency in helping radiologists to detect and diagnose the diseases. Deep learning and transfer learning algorithms are good techniques to detect disease from different image source types such as X-Ray and CT scan images. In this work we used a deep learning technique based on Convolution Neural Network (CNN) to detect and diagnose COVID-19 disease using Chest X-ray images. Moreover, the modified AlexNet architecture is proposed in different scenarios were differing from each other in terms of the type of the pooling layers and/or the number of the neurons that have used in the second fully connected layer. The used chest X-ray images are gathered from two COVID-19 X-ray image datasets and one dataset includes large number of normal and pneumonia X-ray images. With the proposed models we obtained the same or even better result than the original AlexNet with having a smaller number of neurons in the second fully connected layer. https://kjar.spu.edu.iq/index.php/kjar/article/view/523COVID-19, Chest X-Ray Images, CNN, AlexNet, Deep Learning. |
| spellingShingle | Shadman Q. Salih Hawre Kh. Abdulla Zanear Sh. Ahmed Nigar M. Shafiq Surameery Rasper Dh. Rashid Modified AlexNet Convolution Neural Network For Covid-19 Detection Using Chest X-ray Images Kurdistan Journal of Applied Research COVID-19, Chest X-Ray Images, CNN, AlexNet, Deep Learning. |
| title | Modified AlexNet Convolution Neural Network For Covid-19 Detection Using Chest X-ray Images |
| title_full | Modified AlexNet Convolution Neural Network For Covid-19 Detection Using Chest X-ray Images |
| title_fullStr | Modified AlexNet Convolution Neural Network For Covid-19 Detection Using Chest X-ray Images |
| title_full_unstemmed | Modified AlexNet Convolution Neural Network For Covid-19 Detection Using Chest X-ray Images |
| title_short | Modified AlexNet Convolution Neural Network For Covid-19 Detection Using Chest X-ray Images |
| title_sort | modified alexnet convolution neural network for covid 19 detection using chest x ray images |
| topic | COVID-19, Chest X-Ray Images, CNN, AlexNet, Deep Learning. |
| url | https://kjar.spu.edu.iq/index.php/kjar/article/view/523 |
| work_keys_str_mv | AT shadmanqsalih modifiedalexnetconvolutionneuralnetworkforcovid19detectionusingchestxrayimages AT hawrekhabdulla modifiedalexnetconvolutionneuralnetworkforcovid19detectionusingchestxrayimages AT zanearshahmed modifiedalexnetconvolutionneuralnetworkforcovid19detectionusingchestxrayimages AT nigarmshafiqsurameery modifiedalexnetconvolutionneuralnetworkforcovid19detectionusingchestxrayimages AT rasperdhrashid modifiedalexnetconvolutionneuralnetworkforcovid19detectionusingchestxrayimages |