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Skin Cancer Classif...
Skin Cancer Classification based on Cosine Cyclical Learning Rate with Deep Learning
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- Nie, Yali (författare)
- Mittuniversitetet,Institutionen för elektronikkonstruktion
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Carratu, Marco (författare)
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- O'Nils, Mattias, 1969- (författare)
- Mittuniversitetet,Institutionen för elektronikkonstruktion
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Sommella, Paolo (författare)
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Moise, Avoci Uqwiri (författare)
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- Lundgren, Jan, 1977- (författare)
- Mittuniversitetet,Institutionen för elektronikkonstruktion
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(creator_code:org_t)
- IEEE, 2022
- 2022
- Engelska.
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Ingår i: Conference Record - IEEE Instrumentation and Measurement Technology Conference. - : IEEE. - 9781665483605
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Since early-stage skin cancer identification can improve melanoma prognosis and significantly reduce treatment costs, AI-based diagnosis systems might greatly benefit patients suffering from suspicious skin lesions. The study proposes a cosine cyclical learning rate with a skin cancer classification model to improve melanoma prediction. The contributions of models involve three critical CNNs, which are standard deep feature extraction modules for the skin cancer classification in this study (Vgg19, ResNet101 and InceptionV3). Each CNN model applies three different learning rates: fixed learning rate(LR), Cosine Annealing LR, and Cosine Annealing with WarmRestarts. HAM10000 is a large collection of publicly available dermoscopic images dataset used for our experiments. The performance of the proposed approach was appraised through comparative experiments. The outcome has indicated that the proposed method has high efficiency in diagnosing skin lesions with a cosine cyclical learning rate.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorteknik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Engineering (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Cancer och onkologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Cancer and Oncology (hsv//eng)
Nyckelord
- cosine cyclical learning rate
- deep learning
- dermoscopic images
- HAM10000
- skin cancer
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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