Paper Title
Image Segmentation Using Unsupervised Learning
Article Identifiers
Authors
Muskan Rastogi , Farhan Ahmad , Rishabh Pandey , Md Tousif Anwer
Keywords
Abstract
Skin cancer, an unsettling general wellbeing issue, with over 5,000,000 recently recognized cases consistently, simply in the United States. For the most part, skin cancer growth is of two types: Benign and Malignant. Malignant also known as Melanoma. Skin cancer is a typical type of cancer growth, and early identification expands the survival rate. Lots of research has already been done in this field, the best way for the classification is using clustering algorithms. Some of the clustering algorithms are K-means, Fuzzy c means, mountain clustering, etc. But the best one is the k-means clustering algorithm. Clustering is used to identify and group a similar dataset of the image. K-means clustering is the best way to classify remotely sensed imagery.
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"Image Segmentation Using Unsupervised Learning", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.7, Issue 5, page no.1219-1228, May-2022, Available :https://ijnrd.org/papers/IJNRD2205163.pdf
Issue
Volume 7 Issue 5, May-2022
Pages : 1219-1228
Other Publication Details
Paper Reg. ID: IJNRD_181495
Published Paper Id: IJNRD2205163
Downloads: 000121122
Research Area: Science & Technology
Country: Delhi, New Delhi, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2205163.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2205163
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJNRD (IJ Publication) Janvi Wave
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition


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