Can pre-trained convolutional neural networks be directly used as a feature extractor for video-based neonatal sleep and wake classification?

Journal: BMC research notes
Published Date: Nov 4, 2020

Abstract

OBJECTIVE: In this paper, we propose to evaluate the use of pre-trained convolutional neural networks (CNNs) as a features extractor followed by the Principal Component Analysis (PCA) to find the best discriminant features to perform classification using support vector machine (SVM) algorithm for neonatal sleep and wake states using Fluke facial video frames. Using pre-trained CNNs as a feature extractor would hugely reduce the effort of collecting new neonatal data for training a neural network which could be computationally expensive. The features are extracted after fully connected layers (FCL's), where we compare several pre-trained CNNs, e.g., VGG16, VGG19, InceptionV3, GoogLeNet, ResNet, and AlexNet.

Authors

  • Muhammad Awais
    College of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou, 450002, China.
  • Xi Long
    1Department of Electrical EngineeringEindhoven University of Technology5612AZEindhovenThe Netherlands.
  • Bin Yin
    Poultry Institute, Shandong Academy of Agricultural Science, Jinan, Shandong, China.
  • Chen Chen
    The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.
  • Saeed Akbarzadeh
    Center for Intelligent Medical Electronics, Department of Electronic Engineering, School of Information Science and Technology, Fudan University, Shanghai, 200433, China.
  • Saadullah Farooq Abbasi
    Center for Intelligent Medical Electronics, Department of Electronic Engineering, School of Information Science and Technology, Fudan University, Shanghai, 200433, China.
  • Muhammad Irfan
    Department of Pharmaceutics, Faculty of Pharmaceutical Sciences, GC University Faisalabad, Pakistan.
  • Chunmei Lu
    Department of Neonatology, Children's Hospital of Fudan University, Shanghai, 200032, China. luchunmei1975@163.com.
  • Xinhua Wang
    Department of Neurology, Children's Hospital of Fudan University, Shanghai, 200032, China.
  • Laishuan Wang
    Department of Neonatology, Children's Hospital of Fudan University, Shanghai, 200032, China.
  • Wei Chen
    Department of Urology, Zigong Fourth People's Hospital, Sichuan, China.

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