Densemask RCNN: A Hybrid Model for Skin Burn Image Classification and Severity Grading
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software
Link
http://link.springer.com/content/pdf/10.1007/s11063-020-10387-5.pdf
Reference36 articles.
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2. Torpy Janet M, Lynm C, Glass RM (2009) Burn injuries. JAMA 302(16):1828–1928
3. Abraham JP, Plourde BD, Vallez LJ, Nelson-Cheeseman BB, Stark JR, Sparrow EM, Gorman JM (2018) Skin burns. Theory Appl Heat Trans Hum 2:723–739
4. Acha B, Serrano C, Fondón I, Gómez-Cía T (2013) Burn depth analysis using multidimensional scaling applied to psychophysical experiment data. IEEE Trans Med Imaging 32(6):1111–1120
5. Zhai LN, Li J (2015) Prediction methods of skin burn for performance evaluation of thermal protective clothing. Burns 41(7):1385–1396
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