Deepening into the suitability of using pre-trained models of ImageNet against a lightweight convolutional neural network in medical imaging: an experimental study

Deepening into the suitability of using pre-trained models of ImageNet against a lightweight convolutional neural network in medical imaging: an experimental study

Transfer learning (TL) has been widely utilized to address the lack of training data for deep learning models. Specifically, one of the most popular uses of TL has been for the pre-trained models of the ImageNet dataset. Nevertheless, although these pre-trained models have shown an effective perform...

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Bibliographic Details
Main Authors: Laith Alzubaidi, Ye Duan, Ayad Al-Dujaili, Ibraheem Kasim Ibraheem, Ahmed H. Alkenani, Jose Santamaría, Mohammed A. Fadhel, Omran Al-Shamma, Jinglan Zhang
Format: Article
Language:English
Published: PeerJ Inc. 2021-09-01
Series:PeerJ Computer Science
Subjects:
Transfer learning
Deep learning
ImageNet
Convolutional neural network
Medical imaging
Online Access:https://peerj.com/articles/cs-715.pdf

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https://peerj.com/articles/cs-715.pdf

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