Principal Component Analysis Combined with Second Order Statistical Feature Method for Malaria Parasites Classification
The main challenge in detecting malaria parasites is how to identify the subset of relevant features. The objective of this study was to identify a subset of features that are most predictive of malaria parasites using second-order statistical features and principal component analysis methods. Relev...
Main Authors: | Wahab, Iis Hamsir Ayub, Susanto, Adhi, Santosa, Paulus Insap, Tjokronegoro, Maesadji |
---|---|
Format: | Article |
Language: | English |
Published: |
2014
|
Subjects: | |
Online Access: | https://repository.ugm.ac.id/101150/1/2014_JATIT_10May.pdf |
Similar Items
-
Semi Automatic Detector of Plasmodium Falciparum on Microscope Image Based
by: Wahab, Iis Hamsir Ayub, et al.
Published: (2013) -
Identifikasi parasit malaria dalam darah menggunakan metode segmentasi citra digital dan jaringan syaraf tiruan
by: , WAHAB, Iis Hamsir Ayub, et al.
Published: (2008) -
Performance Improvement of Leaf Identification System
Using Principal Component Analysis
by: Kadir, Abdul, et al.
Published: (2012) -
Prediksi Jumlah Kasus Demam Berdarah Dengue Menggunakan Jaringan Syaraf Tiruan (Studi Kasus daerah Kab. Sleman, Provinsi DIY)
by: Iis Hamsir Ayub Wahab
Published: (2016-05-01) -
Real Time Hand Gesture Movements Tracking and Recognizing System
by: Hartanto, Rudy, et al.
Published: (2014)