Dengue Fever Classification Based on Grey Level Co-occurrence Matrix Feature
DOI:
https://doi.org/10.32628/CI001Keywords:
K-means, CMYK-LAB Model, Gray level Co-occurrence Matrix (GLCM), Support Vector Machine (SVM) and Artificial Neural Network (ANN).Abstract
White blood cells have attracted tremendous interest in recent times due to their promise in providing innovative new treatments for a great range of currently debilitating diseases. This is due to their potential ability to regenerate and repair damaged tissue, and hence restore lost body function, in a manner beyond the body’s usual healing process. White blood cells have potential to divide themselves (through mitosis) to produce more White Blood Cells. Any disease that results in cellular and tissue destruction can potentially be treated by WBC cells. Detection of WBC cells has become an important part in modern medicine to diagnose any disease at its prior onset. But due to their characteristics to change their shape, size and colour at different intervals of time it becomes quite difficult to detect and segment them, as this research is going on to detect WBC cells by using the most efficient algorithm among all that have been studied in the literature survey.
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