ITM Web Conf.
Volume 40, 2021International Conference on Automation, Computing and Communication 2021 (ICACC-2021)
|Number of page(s)||5|
|Published online||09 August 2021|
- World Cancer Research Fund on Skin Cancer Statistics. https://www.wcrf.org/dietandcancer/cancer-trends/skin-cancer-statistics. [Google Scholar]
- World Health Organization on Climate Change and Human Health. https://www.who.int/globalchange/climate/summary/en/index7.html [Google Scholar]
- Ichim, Loretta, and Dan Popescu. “Melanoma Detection Using an Objective System Based on Multiple Connected Neural Networks.” IEEE Access 8 (2020): 179189–179202. [CrossRef] [Google Scholar]
- Demyanov, Sergey, et al. “Classification of dermoscopy patterns using deep convolutional neural networks.” 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI). IEEE, 2016. [Google Scholar]
- Majumder, Sharmin, and Muhammad Ahsan Ullah. “Feature extraction from dermoscopy images for an effective diagnosis of melanoma skin cancer.” 2018 10th International Conference on Electrical and Computer Engineering (ICECE). IEEE, 2018. [Google Scholar]
- Eltayef, Khalid, Yongmin Li, and Xiaohui Liu. “Detection of melanoma skin cancer in dermoscopy images.” Journal of Physics: Conference Series. Vol. 787. No. 1. IOP Publishing, 2017. [Google Scholar]
- Jain, Shivangi, and Nitin Pise. “Computer aided melanoma skin cancer detection using image processing.” Procedia Computer Science 48 (2015): 735–740. [CrossRef] [Google Scholar]
- Isasi, A. Gola, B. García Zapirain, and A. Méndez Zorrilla. “Melanomas non-invasive diagnosis application based on the ABCD rule and pattern recognition image processing algorithms.” Computers in Biology and Medicine 41.9 (2011): 742–755. [CrossRef] [Google Scholar]
- She, Zhishun, Y. Liu, and A. Damatoa. “Combination of features from skin pattern and ABCD analysis for lesion classification.” Skin Research and Technology 13.1 (2007): 25–33. [CrossRef] [Google Scholar]
- PH2 Database. https://www.fc.up.pt/addi/ph2\%20database.html [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.