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)
This review article focuses on the role of endoscopy in healthcare as well as the development of automated illness detection using large datasets of endoscopic photographs. The importance of features, the creation and properties of notable public endoscopic datasets, and the challenges of manual diagnosis.
For improved image analysis, extraction and image preparation are all addressed. This paper highlights the usefulness of these algorithms for enhancing the efficiency and accuracy of endoscopic diagnosis. It includes a wide spectrum of illness detection methods, from basic machine learning approaches to advanced deep learning models.
Keywords:
Endoscopy,deep learning,detection
Cite Article:
"Disease Detection In Endoscopic Images By Using Deep Learning", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 5, page no.252 - 257, May-2024, Available :http://www.ijrti.org/papers/IJRTI2405037.pdf
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000205109
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