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ISSN Approved Journal No: 2349-9249 | Impact factor: 8.57 | ESTD Year: 2014
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.57 (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 : 8.57

Issue per Year : 12

Volume Published : 10

Issue Published : 112

Article Submitted : 9452

Article Published : 2428

Total Authors : 6532

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Total Countries : 121

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Published Paper Details
Paper Title: CNN-Based Automated Malaria Parasite Detection From Microscopic Thin Blood Smears Images
Authors Name: Amballa Surya Venkata Prasad , DANNANA BHANU , BOPPANA RAMAKRISHNA , GUDIVADA GOMANTH SAI , KOTCHERLA SAI KUMARI
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TIJER_101653
Published Paper Id: TIJER2303208
Published In: Volume 10 Issue 3, March-2023
DOI:
Abstract: Malaria is a deadly, infectious mosquito borne disease caused by plasmodium parasites. The detection of unicellular protozoan plasmodium parasite which is the cause of malaria takes light microscopic analysis by a skilled practitioner for the diagnosis of malaria. The standard method for diagnosing malaria using light microscopy involves preparing thick and thin blood smears that are stained and examined under a microscope. The major drawback of this approach is its dependence on skilled technicians, of which there is a critical shortage. In this aspect this results in a delay in an inaccurate diagnosis. A reliable alternative is required to enable routine access to high-quality diagnosis, which is currently not available. Deep learning is an artificial intelligence technique where the machine is train to mimic the thought process of a human brain. Our project mainly focusses on building a deep convolutional neural network (CNN) that can detect the malaria parasite infection from thin blood smear samples.
Keywords: CNN, Deep learning, Computer-aided diagnosis
Cite Article: "CNN-Based Automated Malaria Parasite Detection From Microscopic Thin Blood Smears Images", TIJER - International Research Journal (www.tijer.org), ISSN:2349-9249, Vol.10, Issue 3, page no.565-572, March-2023, Available :http://www.tijer.org/papers/TIJER2303208.pdf
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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
Publication Details: Published Paper ID: TIJER2303208
Registration ID:101653
Published In: Volume 10 Issue 3, March-2023
DOI (Digital Object Identifier):
Page No: 565-572
Country: Vizianagaram, Andhra Pradesh, India
Research Area: Science and Technology
Publisher : IJ Publication
Published Paper URL : https://www.tijer.org/viewpaperforall?paper=TIJER2303208
Published Paper PDF: https://www.tijer.org/papers/TIJER2303208
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ISSN: 2349-9249
Impact Factor: 8.57 and ISSN APPROVED
Journal Starting Year (ESTD) : 2014

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