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Cascading YOLO: automated malaria parasite detection for Plasmodium vivax in thin blood smears., , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 11314 of SPIE Proceedings, SPIE, (2020)Parasite Detection in Thick Blood Smears Based on Customized Faster-RCNN on Smartphones., , , , , and . AIPR, page 1-4. IEEE, (2019)CNN-based image analysis for malaria diagnosis., , , , , , , , , and 3 other author(s). BIBM, page 493-496. IEEE Computer Society, (2016)Malaria Thick Blood Smears., , , , , , , , and . (August 2021)Deep Learning for Smartphone-Based Malaria Parasite Detection in Thick Blood Smears., , , , , , , , and . IEEE J. Biomed. Health Informatics, 24 (5): 1427-1438 (2020)Smartphone-Supported Malaria Diagnosis Based on Deep Learning., , , , , and . MLMI@MICCAI, volume 11861 of Lecture Notes in Computer Science, page 73-80. Springer, (2019)Detecting and Segmenting White Blood Cells in Microscopy Images of Thin Blood Smears., , , , , , , , , and . AIPR, page 1-8. IEEE Computer Society, (2017)Detecting and segmenting overlapping red blood cells in microscopic images of thin blood smears., , , , , , , , and . Medical Imaging: Digital Pathology, volume 10581 of SPIE Proceedings, page 105811F. SPIE, (2018)