IJRTI
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)

Call For Paper

For Authors

Forms / Download

Published Issue Details

Editorial Board

Other IMP Links

Facts & Figure

Impact Factor : 8.14

Issue per Year : 12

Volume Published : 11

Issue Published : 118

Article Submitted : 21665

Article Published : 8541

Total Authors : 22459

Total Reviewer : 811

Total Countries : 159

Indexing Partner

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Published Paper Details
Paper Title: A Comprehensive Review on Skin Disease Detection Using Convolutional Neural Networks and Transfer Learning Approaches
Authors Name: Youa Raj Chettri , Anjana Gurung , Manika Gurung , Rahul Shah
Download E-Certificate: Download
Author Reg. ID:
IJRTI_204998
Published Paper Id: IJRTI2506182
Published In: Volume 10 Issue 6, June-2025
DOI:
Abstract: Skin diseases represent a considerable part of the world health problem, as millions of people are affected by skin diseases, and skin diseases are visually similar and without easy access to dermatologists, present problems in terms of diagnostics. Convolutional Neural Networks (CNNs) and Artificial Intelligence (AI) in general have been the game-changer of automated skin disease detection. This paper aims to provide an overview of recent advances in the field of CNN and Transfer Learning (TL) approaches to classifying and diagnosing dermatological diseases based on dermoscopic and clinical images. It discusses datasets, preprocessing pipelines, CNN architectures, performance of different models, existing shortcomings, as well as future works. The key point of this review is to aid in creating AI-based web apps that would provide safe and efficient screening of skin diseases.
Keywords: Skin Disease Detection, Convolutional Neural Networks (CNNs), Transfer Learning, Medical Image Classification, Dermoscopic Image Analysis.
Cite Article: "A Comprehensive Review on Skin Disease Detection Using Convolutional Neural Networks and Transfer Learning Approaches ", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 6, page no.b679-b684, June-2025, Available :http://www.ijrti.org/papers/IJRTI2506182.pdf
Downloads: 000411
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: IJRTI2506182
Registration ID:204998
Published In: Volume 10 Issue 6, June-2025
DOI (Digital Object Identifier):
Page No: b679-b684
Country: gangtok, Sikkim, India
Research Area: Health Science 
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2506182
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2506182
Share Article:

Click Here to Download This Article

Article Preview
Click Here to Download This Article

Major Indexing from www.ijrti.org
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager Academia.edu
arXiv.org : cornell university library Research Gate CiteSeerX DOAJ : Directory of Open Access Journals
DRJI Index Copernicus International Scribd DocStoc

ISSN Details

ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED, Journal Starting Year (ESTD) : 2016

DOI (A digital object identifier)


Providing A digital object identifier by DOI.ONE
How to Get DOI?

Conference

Open Access License Policy

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Creative Commons License This material is Open Knowledge This material is Open Data This material is Open Content

Important Details

Join RMS/Earn 300

IJRTI

WhatsApp
Click Here

Indexing Partner