Classification of skin cancer by means of transfer learning models
Skin cancer is a disease of human skin affected with abberrant or damaged cell and that lead to the formation of tumours. Skin cancer can be mainly classified into melanoma and non-melanoma, where melanoma is more deadly if misdiagnosis at the early stage. Traditional way of skin cancer classificati...
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| Format: | Article |
| Language: | English |
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Penerbit UMP
2021
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| Online Access: | http://umpir.ump.edu.my/id/eprint/34003/ http://umpir.ump.edu.my/id/eprint/34003/1/Classification%20of%20skin%20cancer%20by%20means%20of%20transfer%20learning%20models.pdf |
| _version_ | 1848824397656227840 |
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| author | Lee, Ji Zhe Anwar P. P., Abdul Majeed |
| author_facet | Lee, Ji Zhe Anwar P. P., Abdul Majeed |
| author_sort | Lee, Ji Zhe |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Skin cancer is a disease of human skin affected with abberrant or damaged cell and that lead to the formation of tumours. Skin cancer can be mainly classified into melanoma and non-melanoma, where melanoma is more deadly if misdiagnosis at the early stage. Traditional way of skin cancer classification required dermatologist to classify the cancer based on CT-scan, MRI or X-ray, which may promote risks of misdiagnosis. Hence deep learning is introduced to carry out the image feature extraction for the classification tasks by using the ISIC dataset. With the aids of InceptionV3 on different machine learning model, the skin cancer classification can be carry out by Artificial Intelligence. As a result of this study, Logistic Regression achieved overall classification accuracy of 78.3%, proven it has the ability to classify skin cancer based on skin lesion images |
| first_indexed | 2025-11-15T03:12:23Z |
| format | Article |
| id | ump-34003 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:12:23Z |
| publishDate | 2021 |
| publisher | Penerbit UMP |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-340032022-05-09T08:08:32Z http://umpir.ump.edu.my/id/eprint/34003/ Classification of skin cancer by means of transfer learning models Lee, Ji Zhe Anwar P. P., Abdul Majeed RC Internal medicine T Technology (General) TS Manufactures Skin cancer is a disease of human skin affected with abberrant or damaged cell and that lead to the formation of tumours. Skin cancer can be mainly classified into melanoma and non-melanoma, where melanoma is more deadly if misdiagnosis at the early stage. Traditional way of skin cancer classification required dermatologist to classify the cancer based on CT-scan, MRI or X-ray, which may promote risks of misdiagnosis. Hence deep learning is introduced to carry out the image feature extraction for the classification tasks by using the ISIC dataset. With the aids of InceptionV3 on different machine learning model, the skin cancer classification can be carry out by Artificial Intelligence. As a result of this study, Logistic Regression achieved overall classification accuracy of 78.3%, proven it has the ability to classify skin cancer based on skin lesion images Penerbit UMP 2021 Article PeerReviewed pdf en cc_by_nc_4 http://umpir.ump.edu.my/id/eprint/34003/1/Classification%20of%20skin%20cancer%20by%20means%20of%20transfer%20learning%20models.pdf Lee, Ji Zhe and Anwar P. P., Abdul Majeed (2021) Classification of skin cancer by means of transfer learning models. Mekatronika - Journal of Intelligent Manufacturing & Mechatronics, 3 (2). pp. 77-81. ISSN 2637-0883. (Published) https://doi.org/10.15282/mekatronika.v3i2.7393 https://doi.org/10.15282/mekatronika.v3i2.7393 |
| spellingShingle | RC Internal medicine T Technology (General) TS Manufactures Lee, Ji Zhe Anwar P. P., Abdul Majeed Classification of skin cancer by means of transfer learning models |
| title | Classification of skin cancer by means of transfer learning models |
| title_full | Classification of skin cancer by means of transfer learning models |
| title_fullStr | Classification of skin cancer by means of transfer learning models |
| title_full_unstemmed | Classification of skin cancer by means of transfer learning models |
| title_short | Classification of skin cancer by means of transfer learning models |
| title_sort | classification of skin cancer by means of transfer learning models |
| topic | RC Internal medicine T Technology (General) TS Manufactures |
| url | http://umpir.ump.edu.my/id/eprint/34003/ http://umpir.ump.edu.my/id/eprint/34003/ http://umpir.ump.edu.my/id/eprint/34003/ http://umpir.ump.edu.my/id/eprint/34003/1/Classification%20of%20skin%20cancer%20by%20means%20of%20transfer%20learning%20models.pdf |