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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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)

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Impact Factor : 8.14

Issue per Year : 12

Volume Published : 7

Issue Published : 72

Article Submitted : 2681

Article Published : 1604

Total Authors : 4237

Total Reviewer : 523

Total Countries : 29

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Paper Title: Classification of White Blood Cells from Microscopic Images using CNN
Authors Name: J.Setu Sai Sowmya Kumari , K.ChandraSekharaChari , M.Leelavathi , K.Pavan Kumar , Mrs.N.Rajeswari
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Published Paper Id: IJRTI2107002
Published In: Volume 6 Issue 7, July-2021
Abstract: White Blood Cells also known as leukocytes plays an important role in the human body by increasing the immunity by fighting against infectious diseases. The classification of White Blood Cells, plays an important role in detection of a disease in an individual. The classification can also assist with the identification of diseases like infections, allergies, anemia, leukemia, cancer, Acquired Immune Deficiency Syndrome (AIDS), etc. that are caused due to anomalies in the immune system. This classification will assist the hematologist distinguish the type of White Blood Cells present in human body and find the root cause of diseases.Currently there are a large amount of research going on in this field. Considering a huge potential in the significance of classification of WBCs, a deep learning technique named Convolution Neural Networks (CNN) will be used which can classify the images of WBCs into its subtypes namely, Neutrophil, Eosinophil, Lymphocyte and Monocyte. The results of various experiments executed on the Blood Cell Classification and Detection (BCCD) dataset using CNN are reported in this project.
Keywords: Convolutional Neural Network(CNN), Eosinophil, Lymphocyte, Monocyte, Neutrophil, ReLu, Softmax, Flatten, Max Pooling.
Cite Article: "Classification of White Blood Cells from Microscopic Images using CNN", International Journal of Science & Engineering Development Research (, ISSN:2455-2631, Vol.6, Issue 7, page no.4 - 9, July-2021, Available :
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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
Publication Details: Published Paper ID: IJRTI2107002
Registration ID:181558
Published In: Volume 6 Issue 7, July-2021
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Page No: 4 - 9
Country: Machilipatnam,Krishna, Andhra Pradesh, India
Research Area: Engineering
Publisher : IJ Publication
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

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