Categorization of Integumentary System Disorders using Deep Learning

被引:0
作者
Asish, Madiraju. Sai Ram [1 ]
Sai, Jakka. Mithil [1 ]
Aishwarya, R. [1 ]
Yogitha, R. [1 ]
机构
[1] Sathyabama Inst Sci & Technol, Dept Comp Sci & Engn, Chennai, Tamil Nadu, India
来源
2022 6TH INTERNATIONAL CONFERENCE ON TRENDS IN ELECTRONICS AND INFORMATICS, ICOEI 2022 | 2020年
关键词
Integumentary system; Deep learning; Diagnosing integumentary system diseases; CNN; Image classification; Computer Vision; Transfer Learning; CLASSIFICATION;
D O I
10.1109/ICOEI53556.2022.9776715
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
People in today's world are busy and occupied all of the time. Individuals often overlook minor illnesses in our bodies as a result of our fast-paced lives. Skin disease is one of them. It is the most widespread disease on the planet. People generally consider dermatology problems as ephemeral, though that's not always the case. If the skin disease is not appropriately recognized, it might cause serious complications. The project's current models use segmentation techniques such as edge detection; however, our study seeks to diagnose skin disorders with high accuracy rates utilizing Deep learning. Our goal is to use CNN (convolutional neural networks) and transfer learning from the Inception model to identify and categorize skin disorders. This research seeks to inform victims of the potential repercussions and assist doctors in making an initial diagnosis. This is being implemented in both a web application and an Android application.
引用
收藏
页码:1226 / 1231
页数:6
相关论文
共 35 条
[1]   Discriminative Feature Learning for Skin Disease Classification Using Deep Convolutional Neural Network [J].
Ahmad, Belal ;
Usama, Mohd ;
Huang, Chuen-Min ;
Hwang, Kai ;
Hossain, M. Shamim ;
Muhammad, Ghulam .
IEEE ACCESS, 2020, 8 :39025-39033
[2]  
Ajith A, 2017, 2017 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICICCS), P168, DOI 10.1109/ICCONS.2017.8250703
[3]  
[Anonymous], 2020, 2020 6 INT C SCI, P133, DOI DOI 10.1109/ICSITech49800.2020.9392030
[4]   Skin diseases among adolescent boys in Abha, Saudi Arabia [J].
Bahamdan, K ;
Mahfouz, AAR ;
Tallab, T ;
Badawi, IA ;
AlAmari, OM .
INTERNATIONAL JOURNAL OF DERMATOLOGY, 1996, 35 (06) :405-407
[5]   Skin disease detection and segmentation using dynamic graph cut algorithm and classification through Naive Bayes classifier [J].
Balaji, V. R. ;
Suganthi, S. T. ;
Rajadevi, R. ;
Kumar, V. Krishna ;
Balaji, B. Saravana ;
Pandiyan, Sanjeevi .
MEASUREMENT, 2020, 163
[6]  
Chakraborty S, 2017, 2017 IEEE 8TH ANNUAL UBIQUITOUS COMPUTING, ELECTRONICS AND MOBILE COMMUNICATION CONFERENCE (UEMCON), P242, DOI 10.1109/UEMCON.2017.8249038
[7]  
Chakraborty S, 2017, 2017 8TH ANNUAL INDUSTRIAL AUTOMATION AND ELECTROMECHANICAL ENGINEERING CONFERENCE (IEMECON), P224, DOI 10.1109/IEMECON.2017.8079594
[8]   Psoriasis - epidemiology and clinical spectrum [J].
Christophers, E .
CLINICAL AND EXPERIMENTAL DERMATOLOGY, 2001, 26 (04) :314-320
[9]  
Diame Zahraa E., 2021, 2021 International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC), P324, DOI 10.1109/MIUCC52538.2021.9447615
[10]   Robust feature spaces from pre-trained deep network layers for skin lesion classification [J].
dos Santos, Fernando Pereira ;
Ponti, Moacir A. .
PROCEEDINGS 2018 31ST SIBGRAPI CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI), 2018, :189-196