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

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

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) algorith...

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Bibliographic Details
Main Authors: Muhammad Awais, Xi Long, Bin Yin, Chen Chen, Saeed Akbarzadeh, Saadullah Farooq Abbasi, Muhammad Irfan, Chunmei Lu, Xinhua Wang, Laishuan Wang, Wei Chen
Format: Article
Language:English
Published: BMC 2020-11-01
Series:BMC Research Notes
Subjects:
Convolutional neural networks (CNNs)
Video electroencephalogram (VEEG)
Neonatal sleep
Sleep and wake classification
Feature extraction
Online Access:http://link.springer.com/article/10.1186/s13104-020-05343-4

Internet

http://link.springer.com/article/10.1186/s13104-020-05343-4

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