Unsupervised learning of image data using generative adversarial network
Over the past few years, with the introduction of deep learning techniques such as convolution neural network (CNN), supervised learning with CNN had achieved a huge success in the computer vision area such as classifying digital images. However, supervised learning has a major drawback, in which it...
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| Main Authors: | , |
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| Format: | Proceedings |
| Language: | English English |
| Published: |
Springer, Singapore
2020
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| Subjects: | |
| Online Access: | https://eprints.ums.edu.my/id/eprint/27636/1/Unsupervised%20learning%20of%20image%20data%20using%20generative%20adversarial%20network-Abstract.pdf https://eprints.ums.edu.my/id/eprint/27636/2/Unsupervised%20learning%20of%20image%20data%20using%20generative%20adversarial%20network.pdf https://eprints.ums.edu.my/id/eprint/27636/ https://www.scopus.com/record/display.uri?eid=2-s2.0-85077110455&origin=inward&txGid=91854adc5da594e451d75d9e8b135132 |
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https://eprints.ums.edu.my/id/eprint/27636/1/Unsupervised%20learning%20of%20image%20data%20using%20generative%20adversarial%20network-Abstract.pdfhttps://eprints.ums.edu.my/id/eprint/27636/2/Unsupervised%20learning%20of%20image%20data%20using%20generative%20adversarial%20network.pdf
https://eprints.ums.edu.my/id/eprint/27636/
https://www.scopus.com/record/display.uri?eid=2-s2.0-85077110455&origin=inward&txGid=91854adc5da594e451d75d9e8b135132