An XNet-CNN Diabetic Retinal Image Classification Method
In this research,a retina image automatic recognition system based on Convolutional Neural Network (CNN) is proposed for the disadvantages of the traditional retina image processing process which is cumbersome and poor in robustness. First, image preprocessing includes noise removal, numerical norma...
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| Format: | Article |
| Language: | zho |
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Harbin University of Science and Technology Publications
2020-02-01
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| Series: | Journal of Harbin University of Science and Technology |
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| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1823 |
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| _version_ | 1849399191075291136 |
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| author | CHEN Yu ZHOU Yujia DING Hui |
| author_facet | CHEN Yu ZHOU Yujia DING Hui |
| author_sort | CHEN Yu |
| collection | DOAJ |
| description | In this research,a retina image automatic recognition system based on Convolutional Neural Network (CNN) is proposed for the disadvantages of the traditional retina image processing process which is cumbersome and poor in robustness. First, image preprocessing includes noise removal, numerical normalization, and data volume amplification; then, a new neural network model, XNet, is designed. XNet inherits the advantages of LeNet and Inception networks. The network parameters are based on training. The samples were adjusted adaptively. Finally, the comparison of accuracy and number of iterations was performed for different network structures. The experimental results show that the XNet network structure is superior to LeNet and Inception, and the accuracy rate can reach 91%; and the necessity of data amplification is confirmed through experiments. |
| format | Article |
| id | doaj-art-0e65f798cf5048cf9bb0341463374784 |
| institution | Kabale University |
| issn | 1007-2683 |
| language | zho |
| publishDate | 2020-02-01 |
| publisher | Harbin University of Science and Technology Publications |
| record_format | Article |
| series | Journal of Harbin University of Science and Technology |
| spelling | doaj-art-0e65f798cf5048cf9bb03414633747842025-08-20T03:38:24ZzhoHarbin University of Science and Technology PublicationsJournal of Harbin University of Science and Technology1007-26832020-02-012501737910.15938/j.jhust.2020.01.011An XNet-CNN Diabetic Retinal Image Classification MethodCHEN Yu0ZHOU Yujia1DING Hui2School of Information and Computer Engineering of Northeast Forestry University, Harbin 150040, ChinaSchool of Information and Computer Engineering of Northeast Forestry University, Harbin 150040, ChinaHainan Eye Hospital, Haikou 570100, ChinaIn this research,a retina image automatic recognition system based on Convolutional Neural Network (CNN) is proposed for the disadvantages of the traditional retina image processing process which is cumbersome and poor in robustness. First, image preprocessing includes noise removal, numerical normalization, and data volume amplification; then, a new neural network model, XNet, is designed. XNet inherits the advantages of LeNet and Inception networks. The network parameters are based on training. The samples were adjusted adaptively. Finally, the comparison of accuracy and number of iterations was performed for different network structures. The experimental results show that the XNet network structure is superior to LeNet and Inception, and the accuracy rate can reach 91%; and the necessity of data amplification is confirmed through experiments.https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1823convolution neural networkdeep learningretinal images classificationdiabetic retinal images |
| spellingShingle | CHEN Yu ZHOU Yujia DING Hui An XNet-CNN Diabetic Retinal Image Classification Method Journal of Harbin University of Science and Technology convolution neural network deep learning retinal images classification diabetic retinal images |
| title | An XNet-CNN Diabetic Retinal Image Classification Method |
| title_full | An XNet-CNN Diabetic Retinal Image Classification Method |
| title_fullStr | An XNet-CNN Diabetic Retinal Image Classification Method |
| title_full_unstemmed | An XNet-CNN Diabetic Retinal Image Classification Method |
| title_short | An XNet-CNN Diabetic Retinal Image Classification Method |
| title_sort | xnet cnn diabetic retinal image classification method |
| topic | convolution neural network deep learning retinal images classification diabetic retinal images |
| url | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1823 |
| work_keys_str_mv | AT chenyu anxnetcnndiabeticretinalimageclassificationmethod AT zhouyujia anxnetcnndiabeticretinalimageclassificationmethod AT dinghui anxnetcnndiabeticretinalimageclassificationmethod AT chenyu xnetcnndiabeticretinalimageclassificationmethod AT zhouyujia xnetcnndiabeticretinalimageclassificationmethod AT dinghui xnetcnndiabeticretinalimageclassificationmethod |