Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Malaria is a disease that, despite having been around for more than quite a while, continues to ensure innumerable lives consistently. The movement of man-made intellectual ability has arranged for the progression of novel wilderness fever treatment methods. We are acquainting AI approaches with this field in this venture, which can be useful in illness counteraction, discovery, and treatment. In view of the grouping of meager blood smear images of possibly contaminated cells, convolutional brain networks for malaria identification are created. We present image handling strategies for portioning red platelets from entire slide images. We likewise utilize the Support Vector Machine (SVM), a directed AI calculation that can be applied to both grouping and relapse issues.
Keywords:
Deep Convolutional Neural Network, Diagnosis, Malaria Cell images, Support Vector Machine
Cite Article:
"Classification of Malaria Cells", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 7, page no.608 - 611, July-2022, Available :http://www.ijrti.org/papers/IJRTI2207085.pdf
Downloads:
000204863
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator