Open Access
| Issue |
E3S Web Conf.
Volume 645, 2025
The 1st International Conference on Green Engineering for Sustainable Future (ICoGESF 2025)
|
|
|---|---|---|
| Article Number | 04003 | |
| Number of page(s) | 8 | |
| Section | Automation and Smart Manufacturing | |
| DOI | https://doi.org/10.1051/e3sconf/202564504003 | |
| Published online | 28 August 2025 | |
- Ferrari A.J., Santomauro D.F., Aali A., et al (2024) Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet 403:2133-2161. https://doi.org/10.1016/S0140-6736(24)00757-8 [Google Scholar]
- Yakupu A., Aimaier R., Yuan B., et al (2023) The burden of skin and subcutaneous diseases: findings from the global burden of disease study 2019. Front Public Health 11:. https://doi.org/10.3389/fpubh.2023.1145513 [Google Scholar]
- Codella N.C.F., Gutman D., Celebi M.E., et al (2018) Skin lesion analysis toward melanoma detection: A challenge at the 2017 International symposium on biomedical imaging (ISBI), hosted by the international skin imaging collaboration (ISIC). In: 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018). pp 168-172 [Google Scholar]
- Singh V., Sultanpure K.A., Patil H. (2024) Frontier machine learning techniques for melanoma skin cancer identification and categorization: An in-Depth review. Oral Oncology Reports 9:100217. https://doi.org/10.1016/j.oor.2024.100217 [Google Scholar]
- Ferlay J., Colombet M., Soerjomataram I., et al (2021) Cancer statistics for the year 2020: An overview. Int J Cancer 149:778-789. https://doi.org/10.1002/ijc.33588 [Google Scholar]
- American Cancer Society (2023) Melanoma Skin Cancer Early Detection, Diagnosis, and Staging. In: https://www.cancer.org/cancer/types/melanoma-skincancer/detection-diagnosis-staging/signs-and-symptoms.html.www.cancer.org/cancer/risk-prevention/sun-and-uv/skin-exams.html [Google Scholar]
- Yilmaz A., Kalebasi M., Samoylenko Y., et al (2021) Benchmarking of Lightweight Deep Learning Architectures for Skin Cancer Classification using ISIC 2017 Dataset [Google Scholar]
- Zafar K., Gilani S.O., Waris A., et al (2020) Skin lesion segmentation from dermoscopic images using convolutional neural network. Sensors (Switzerland) 20:. https://doi.org/10.3390/s20061601 [Google Scholar]
- Jojoa Acosta M.F., Caballero Tovar L.Y., Garcia-Zapirain M.B., Percybrooks W.S. (2021) Melanoma diagnosis using deep learning techniques on dermatoscopic images. BMC Med Imaging 21:. https://doi.org/10.1186/s12880-020-00534-8 [Google Scholar]
- Goyal M., Oakley A., Bansal P., et al (2020) Skin Lesion Segmentation in Dermoscopic Images with Ensemble Deep Learning Methods. IEEE Access 8:4171-4181. https://doi.org/10.1109/ACCESS.2019.2960504 [Google Scholar]
- Tammina S. (2019) Transfer learning using VGG-16 with Deep Convolutional Neural Network for Classifying Images. International Journal of Scientific and Research Publications (IJSRP) 9:p 9420. https://doi.org/10.29322/ijsrp.9.10.2019.p9420 [Google Scholar]
- Radiuk P.M. (2018) Impact of Training Set Batch Size on the Performance of Convolutional Neural Networks for Diverse Datasets. Information Technology and Management Science 20:. https://doi.org/10.1515/itms-2017-0003 [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.