Smartphone-Supported Malaria Diagnosis Based on Deep Learning
© 2019, Springer Nature Switzerland AG. Malaria remains a major burden on global health, causing about half a million deaths every year. The objective of this work is to develop a fast, automated, smartphone-supported malaria diagnostic system. Our proposed system is the first system using both imag...
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| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Conference or Workshop Item |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://repository.li.mahidol.ac.th/handle/123456789/50691 |
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| Institution: | Mahidol University |