Automated Detection of Marine Mammal Species based on Short-Time Fractional Fourier Transform

被引：0
|
作者：
Zhang, Xiaowei [1 ]
Liu, Ziyuan [1 ]
Wang, Wenchao [1 ]
Xu, Ji [1 ]
机构：
[1] Univ Chinese Acad Sci, Inst Acoust, Key Lab Speech Acoust & Content Understand, Beijing, Peoples R China
来源：
OCEANS 2021: SAN DIEGO - PORTO | 2021年
关键词：
deep learning; underwater target identification; linear frequency-modulated pulse; fractional Fourier transform; POPULATION; ECOLOGY;
D O I：
暂无
中图分类号：
U6 [水路运输]; P75 [海洋工程];
学科分类号：
0814 ; 081505 ; 0824 ; 082401 ;
摘要：
Upcalls are the classic feature of the ocean animals in the underwater target identification, as are restricted by background noise and vocalizations from other organism. The fractional Fourier transform (FRFT) has a good recognition capability for upcalls, since they sound like linear frequency-modulated pulses. By optimizing feature extraction methods by the fractional Fourier transform (FRFT), we train the convolutional Neural Network to recognize the upcalls signal, and improve the accuracy from 96.9% to 97.8%
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页数：5
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