Asymmetric Kernel Convolutional Neural Network for Acoustic Scenes Classification

被引：0

作者：

Wang, Chien-Yao ^{[1
]}

Wang, Jia-Ching ^{[1
]}

Wu, Yu-Chi ^{[2
]}

Chang, Pao-Chi ^{[2
]}

机构：

[1] Natl Cent Univ, Dept Comp Sci & Informat Engn, Jhongli, Taiwan

[2] Natl Cent Univ, Dept Commun Engn, Jhongli, Taiwan

来源：

2017 IEEE INTERNATIONAL SYMPOSIUM ON CONSUMER ELECTRONICS (ISCE) | 2017年

关键词：

acoustic scenes classification; deep learning; convolutional neural network;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this work, we propose an Asymmetric Kernel Convolutional Neural Network (AKCNN) for Acoustic Scenes Classification (ASC). Its kernel shape is not the traditional square but asymmetric in width and height. It also uses Weight Normalization (WN) to accelerate the training process because it can early converge the training loss and accuracy. The best of all, WN can help increase the accuracy of ASC. TUT Acoustic Scenes 2016 Dataset [1] is used for evaluation. The result shows that AKCNN achieves accuracy 86.7%. If we rank the score in DCASE2016 ASC Challenge, it shows that the system would have a higher score than the 5th place.

引用

页码：11 / 12

页数：2

共 50 条

[21] Optimized convolutional neural network for the classification of lung cancer
Divya Paikaray
Ashok Kumar Mehta
Danish Ali Khan
The Journal of Supercomputing, 2024, 80 : 1973 - 1989
[22] A novel deep convolutional neural network for arrhythmia classification
Dang, Hao
Sun, Muyi
Zhang, Guanhong
Zhou, Xiaoguang
Chang, Qing
Xu, Xiangdong
2019 INTERNATIONAL CONFERENCE ON ADVANCED MECHATRONIC SYSTEMS (ICAMECHS), 2019, : 7 - 11
[23] Classification of Trackside Equipment Based on Convolutional Neural Network
Li, Weidong
Li, Jinshuang
Liu, Yang
PROCEEDINGS OF THE 32ND 2020 CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2020), 2020, : 4806 - 4811
[24] CONVOLUTIONAL NEURAL NETWORK BASED CLASSIFICATION FOR HYPERSPECTRAL DATA
Jia, Peiyuan
Zhang, Miao
Yu, Wenbo
Shen, Fei
Shen, Yi
2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2016, : 5075 - 5078
[25] Quantum convolutional neural network for classical data classification
Hur, Tak
Kim, Leeseok
Park, Daniel K.
QUANTUM MACHINE INTELLIGENCE, 2022, 4 (01)
[26] Optimized convolutional neural network for the classification of lung cancer
Paikaray, Divya
Mehta, Ashok Kumar
Khan, Danish Ali
JOURNAL OF SUPERCOMPUTING, 2024, 80 (02) : 1973 - 1989
[27] Vehicle Type Classification Using Convolutional Neural Network
Hicham, Bensedik
Ahmed, Azough
Mohammed, Meknasssi
2018 IEEE 5TH INTERNATIONAL CONGRESS ON INFORMATION SCIENCE AND TECHNOLOGY (IEEE CIST'18), 2018, : 313 - 316
[28] WOODEN DOWELS CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORK
Paulauskaite-Taraseviciene, Agne
Sutiene, Kristina
Pipiras, Laurynas
PROCEEDINGS OF THE ROMANIAN ACADEMY SERIES A-MATHEMATICS PHYSICS TECHNICAL SCIENCES INFORMATION SCIENCE, 2019, 20 (04): : 401 - 408
[29] Improved Breast Cancer Classification Through Combining Graph Convolutional Network and Convolutional Neural Network
Zhang, Yu-Dong
Satapathy, Suresh Chandra
Guttery, David S.
Manuel Gorriz, Juan
Wang, Shui-Hua
INFORMATION PROCESSING & MANAGEMENT, 2021, 58 (02)
[30] Pathological brain classification using multiple kernel-based deep convolutional neural network
Dora, Lingraj
Agrawal, Sanjay
Panda, Rutuparna
Pachori, Ram Bilas
NEURAL COMPUTING & APPLICATIONS, 2023, 36 (2) : 747 - 756

← 1 2 3 4 5 →