Hartati et al., 2019 Image Dataset
Article Title: Performance of SVM and ANFIS for Classification of Malaria Parasite and Its Life-Cycle-Stages in Blood Smear
Article Link: ref
Description
It is a thin, Giemsa-stained blood smear image dataset
Demography
- Country: Indonesia
- City: Jakarta
- Study Area: Bina Medical Support Services (BPPM)
- Parasite’s species: Plasmodium malariae, Plasmodium falciparum, Plasmodium vivax,
Imaging Technique
- Number of Images: 600 images
- Image Resolution: 2560 x 1920
Dataset Availability
| Corresponding Author | DOI |
|---|---|
| Sri Hartati (shartati@ugm.ac.id) | https://doi.org/10.1007/978-981-13-3441-2_9 |
Cite this article
❗🛑 If you are using this resource, please cite:
Hartati, S., Harjoko, A., Rosnelly, R., Chandradewi, I., Faizah (2019). Performance of SVM and ANFIS for Classification of Malaria Parasite and Its Life-Cycle-Stages in Blood Smear. In: Yap, B., Mohamed, A., Berry, M. (eds) Soft Computing in Data Science. SCDS 2018. Communications in Computer and Information Science, vol 937. Springer, Singapore. https://doi.org/10.1007/978-981-13-3441-2_9