A Machine Learning Framework for Hair Type Categorization to Optimize the Hair Removal Algorithm in Dermatoscopy Images-Reference-Cited by-同舟云学术

A Machine Learning Framework for Hair Type Categorization to Optimize the Hair Removal Algorithm in Dermatoscopy Images

Published:2023-12-07 Issue: Volume:abs/1710.05006 Page:121-122
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Container-title:2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology
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Author:

Ioannidis Georgios S.¹,Trivizakis Eleftherios¹,Krasagakis Konstantinos²,Lallas Aimilios³,Apalla Zoe⁴,Evangelou Georgios²,Marias Kostas¹

Affiliation:

1. Computational Biomedicine Laboratory of Foundation for Research and Technology Hellas,Heraklion,Greece

2. University Hospital of Heraklion,Department of Dermatology,Heraklion,Greece

3. Aristotle University,School of Medicine, Faculty of Health Sciences,First Department of Dermatology,Thessaloniki,Greece

4. Aristotle University of Thessaloniki,Second Dermatology Department,Greece

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10404092/10404107/10404510.pdf?arnumber=10404510

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4. Computational Radiomics System to Decode the Radiographic Phenotype

5. A novel deep learning architecture outperforming ‘off‑the‑shelf’ transfer learning and feature‑based methods in the automated assessment of mammographic breast density