IMPLEMENTATION OF BLOOD CELL USING DEEP LEARNING
Keerthana.B
, Sandhiya.R , SrinithiSneha.K.B
Blood Cells ,WBC, Deep Learning
Leukocytes, commonly known as white blood cells, are vital for the body's defense against infectious diseases and for boosting immunity. In order to identify an illness in a person, the classification of white blood cells is crucial.
The classification can help with the diagnosis of illnesses like infections, allergies, leukemia, cancer, AIDS, anemia, and other conditions brought on by immune system abnormalities. The hematologist will utilize this classification to identify the different types of White Blood Cells in the human body and identify the underlying causes of disorders. We will be utilizing the deep learning technique Convolution Neural Networks (CNN), which can classify the images of WBCs into its subtypes, namely, Neutrophil, Eosinophil, Lymphocyte, and Monocyte, due to the enormous potential in the relevance of WBC classification. The Blood Cell Classification and detection dataset will be used in this paper to present the findings of several experiments.
"IMPLEMENTATION OF BLOOD CELL USING DEEP LEARNING", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.11, Issue 2, page no.446-452, February-2024, Available :https://tijer.org/TIJER/papers/TIJERB001069.pdf
Volume 11
Issue 2,
February-2024
Pages : 446-452
Paper Reg. ID: TIJER_151059
Published Paper Id: TIJERB001069
Downloads: 000275
Research Area: Science and Technology
Country: Tiruvallur, Tamil Nadu, India
ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER (IJ Publication) Janvi Wave
