Convolutional Neural Networks Using MobileNet for Skin Lesion Classification

被引：0
|
作者：
Sae-Lim, Wannipa [1 ]
Wettayaprasit, Wiphada [1 ]
Aiyarak, Pattara [1 ]
机构：
[1] Prince Songkla Univ, Dept Comp Sci, Artificial Intelligence Res Lab, Hat Yai, Thailand
来源：
2019 16TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER SCIENCE AND SOFTWARE ENGINEERING (JCSSE 2019) | 2019年
关键词：
deep neural networks; convolutional neural networks; image processing; skin lesion classification; MobileNet; DEEP; SEGMENTATION; DIAGNOSIS;
D O I：
10.1109/jcsse.2019.8864155
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
Skin lesion classification is a particular interesting area of research in dermatoscopic lesion image processing. In this paper, we present a skin lesion classification approach based on the light weight deep Convolutional Neural Networks (CNNs), called MobileNet. We employed MobileNet and proposed the modified MobileNet for skin lesion classification. For the evaluation of our model, we had used the official dataset of Human Against Machine with 10,000 training images (HAM 10000) which was a collection of multisource dermatoscopic images. Data up-sampling and data augmentation method were used in our study for improving the efficiency of the classifier. The comparison results showed that our modified model had achieved higher accuracy, specificity, sensitivity, and F1-score than the traditional MobileNet.
引用
收藏
页码：242 / 247
页数：6
相关论文
共 50 条
  • [21] Classification of pulmonary tuberculosis lesion with convolutional neural networks
    Karnkawinpong, T.
    Limpiyakorn, Y.
    2018 11TH INTERNATIONAL CONFERENCE ON COMPUTER AND ELECTRICAL ENGINEERING, 2019, 1195
  • [22] Automated plant leaf disease detection and classification using optimal MobileNet based convolutional neural networks
    Ashwinkumar, S.
    Rajagopal, S.
    Manimaran, V
    Jegajothi, B.
    MATERIALS TODAY-PROCEEDINGS, 2022, 51 : 480 - 487
  • [23] Skin Lesion Classification Using Collective Intelligence of Multiple Neural Networks
    Popescu, Dan
    El-khatib, Mohamed
    Ichim, Loretta
    SENSORS, 2022, 22 (12)
  • [24] Skin Cancer Classification Using Convolutional Neural Networks: Systematic Review
    Brinker, Titus Josef
    Hekler, Achim
    Utikal, Jochen Sven
    Grabe, Niels
    Schadendorf, Dirk
    Klode, Joachim
    Berking, Carola
    Steeb, Theresa
    Enk, Alexander H.
    von Kalle, Christof
    JOURNAL OF MEDICAL INTERNET RESEARCH, 2018, 20 (10)
  • [25] Skin Cancer Classification Using Different Backbones of Convolutional Neural Networks
    Huynh, Anh T.
    Van-Dung Hoang
    Vu, Sang
    Le, Trong T.
    Nguyen, Hien D.
    ADVANCES AND TRENDS IN ARTIFICIAL INTELLIGENCE: THEORY AND PRACTICES IN ARTIFICIAL INTELLIGENCE, 2022, 13343 : 160 - 172
  • [26] Optimized Convolutional Neural Network Models for Skin Lesion Classification
    Villa-Pulgarin, Juan Pablo
    Ruales-Torres, Anderson Alberto
    Arias-Garzon, Daniel
    Bravo-Ortiz, Mario Alejandro
    Arteaga-Arteaga, Harold Brayan
    Mora-Rubio, Alejandro
    Alzate-Grisales, Jesus Alejandro
    Mercado-Ruiz, Esteban
    Hassaballah, M.
    Orozco-Arias, Simon
    Cardona-Morales, Oscar
    Tabares-Soto, Reinel
    CMC-COMPUTERS MATERIALS & CONTINUA, 2022, 70 (02): : 2131 - 2148
  • [27] Convolutional Neural Network based Skin Lesion Classification and Identification
    Aishwarya, U.
    Daniel, I. Jackson
    Raghul, R.
    PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON INVENTIVE COMPUTATION TECHNOLOGIES (ICICT-2020), 2020, : 264 - 270
  • [28] Depthwise Separable Convolutional Neural Network for Skin Lesion Classification
    Kassani, Sara Hosseinzadeh
    Kassani, Peyman Hosseinzadeh
    Wesolowski, Michal J.
    Schneider, Kevin A.
    Deters, Ralph
    2019 IEEE 19TH INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND INFORMATION TECHNOLOGY (ISSPIT 2019), 2019,
  • [29] DermaDL: Advanced Convolutional Neural Networks for Computer-Aided Skin-Lesion Classification
    Lima D.M.
    Rodrigues-Jr J.F.
    Brandoli B.
    Goeuriot L.
    Amer-Yahia S.
    SN Computer Science, 2021, 2 (4)
  • [30] Skin lesion classification of dermoscopic images using machine learning and convolutional neural network
    Shetty, Bhuvaneshwari
    Fernandes, Roshan
    Rodrigues, Anisha P.
    Chengoden, Rajeswari
    Bhattacharya, Sweta
    Lakshmanna, Kuruva
    SCIENTIFIC REPORTS, 2022, 12 (01)
12345