演講題目：Classifying Shark Behavior in Time and Frequency Domain using CNN and RNN

演  講   者：Prof. Hen-Geul Yeh, California State University, Long Beach, CA, USA

時　　間：2022/11/3, Thursday 14:00~16:00

地　　點：清華大學台達館304室 (Delta Building R304)

ABSTRACT

This paper uses accelerometer data from California horn sharks obtained from the Shark Lab at California State University, Long Beach, (CSULB) to create a behavior classifier using deep convolutional neural networks (CNN) and recurrent neural networks (RNN). The data consists of motion samples in six degrees of freedom, which were visually observed and classified into four categories: feeding, swimming, resting, and nondeterministic motion (NDM). We process 2-, 5-, and 10-seconds snapshots in the time and frequency domains, which are fed into the neural network’s toolbox to train classifiers. It is observed that the performance of both models is drastically improved when the frequency domain data is applied in the deep neural network.

BIOGRAPHY

Hen-Geul Yeh (SM’82) received the B.S. degree in engineering science from National Chen Kung University, Taiwan, ROC (1978), and the M.S. degree in mechanical engineering (1979) and the Ph.D. degree in electrical engineering from the University of California, Irvine (1982), respectively.

Since 1983, he has been with the Electrical Engineering department at California State University, Long Beach (CSULB), USA, and served as the department Chair from 2016 to 2022.

Dr. Yeh is the recipient of IEEE R6 Outstanding Engineering Educator Award for outstanding contribution to the education of electrical engineers in the areas of DSP, Green Energy, and smart systems in 2019, seven US patents and applications. Since 2010, he has served as the Founder and Chair of IEEE Green Energy and Smart Systems Conference (IGESSC).