Hybrid Loss-Constrained Lightweight Convolutional Neural Networks for Cervical Cell Classification

Artificial intelligence (AI) technologies have resulted in remarkable achievements and conferred massive benefits to computer-aided systems in medical imaging. However, the worldwide usage of AI-based automation-assisted cervical cancer screening systems is hindered by computational cost and resourc...

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Bibliographic Details
Main Authors:	Chen, W. (Author), Gao, L. (Author), Li, X. (Author), Shen, W. (Author)
Format:	Article
Language:	English
Published:	MDPI 2022
Subjects:	Cancer diagnosis Cell classification Cervical cancer diagnose cervical cancer diagnosis Cervical cancers Cervical cells Computer aided diagnosis Convolution Convolutional neural network Convolutional neural networks deep learning Deep learning Diseases hybrid loss function Hybrid loss function Lightweight convolutional neural network lightweight convolutional neural networks Loss functions medical imaging Medical imaging
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Hybrid Loss-Constrained Lightweight Convolutional Neural Networks for Cervical Cell Classification

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