Notice of retraction
Vol. 32, No. 8(2), S&M2292

ISSN (print) 0914-4935
ISSN (online) 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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S&M2355 Research Paper of Special Issue

Computed Tomography Image Recognition with Convolutional Neural Network Using Wearable Sensors

Yuqing He, Lei Lei, Guangsong Yang, Chih-Cheng Chen, Christopher Chun Ki Chan, and Kuei-Kuei Lai

(Received April 22, 2020; Accepted August 12, 2020)

Keywords: convolutional neural network, CT image recognition; diagnosis support, overfitting

We propose a modified convolutional neural network (CNN) tailor-made for computed tomography (CT) image disease recognition to assist doctors in disease diagnosis. First, we analyze the effects of varying the CNN activation function and pooling parameters and analyze the CNN’s performance using one data set. Second, we address the activation error that occurs when the sample data size is increased by preprocessing images by an enhancement technique, adjusting the activation function and initialization weighting, training/testing the target, and adaptively extracting features. We found that our method alleviates overfitting with these techniques. The experimental results show that our proposed scheme improves the recognition rate and can better generalize findings.

Corresponding author: Guangsong Yang, Chih-Cheng Chen




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