Zobrazeno 1 - 10
of 466
pro vyhledávání: '"ZHAO, YUANJUN"'
Autor:
Liu, Zheng, Huang, Na, Han, Chunjia, Yang, Mu, Zhao, Yuanjun, Sun, Wenzhuo, Arya, Varsha, Gupta, Brij B., Shi, Lihua
Publikováno v:
British Food Journal, 2024, Vol. 126, Issue 6, pp. 2477-2499.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/BFJ-12-2023-1089
Autor:
Zhao, Yuanjun, Zhou, Xin, Yang, Zihao, Hasegawa, Shingo, Motokura, Ken, Wang, Zhaozhan, Yu, Bo, Shi, Xiaolin, Xu, Guoqiang, Ding, Xin, Yang, Yong
Publikováno v:
In Chemical Engineering Journal 15 December 2024 502
Publikováno v:
In International Review of Financial Analysis November 2024 96 Part A
Autor:
Zhao, Yuanjun, Gao, Mengqiu, Qin, Yanyang, Da, Xinyu, Deng, Xuetian, Jia, Xin, Xi, Kai, Su, Yaqiong, Ding, Shujiang, Rong, Qiang, Kong, Xiangpeng, Gao, Guoxin
Publikováno v:
In Chemical Engineering Journal 1 September 2024 495
Autor:
Guan, Zhigui, Zhao, Yuanjun
Publikováno v:
In International Review of Economics and Finance September 2024 95
Autor:
Yen, Hao, Yang, Chao-Han Huck, Hu, Hu, Siniscalchi, Sabato Marco, Wang, Qing, Wang, Yuyang, Xia, Xianjun, Zhao, Yuanjun, Wu, Yuzhong, Wang, Yannan, Du, Jun, Lee, Chin-Hui
We propose a novel neural model compression strategy combining data augmentation, knowledge transfer, pruning, and quantization for device-robust acoustic scene classification (ASC). Specifically, we tackle the ASC task in a low-resource environment
Externí odkaz:
http://arxiv.org/abs/2107.01461
Publikováno v:
In Chemical Engineering Journal 15 March 2024 484
Spoofing attacks posed by generating artificial speech can severely degrade the performance of a speaker verification system. Recently, many anti-spoofing countermeasures have been proposed for detecting varying types of attacks from synthetic speech
Externí odkaz:
http://arxiv.org/abs/2012.03154
Autor:
Hu, Hu, Yang, Chao-Han Huck, Xia, Xianjun, Bai, Xue, Tang, Xin, Wang, Yajian, Niu, Shutong, Chai, Li, Li, Juanjuan, Zhu, Hongning, Bao, Feng, Zhao, Yuanjun, Siniscalchi, Sabato Marco, Wang, Yannan, Du, Jun, Lee, Chin-Hui
Publikováno v:
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
To improve device robustness, a highly desirable key feature of a competitive data-driven acoustic scene classification (ASC) system, a novel two-stage system based on fully convolutional neural networks (CNNs) is proposed. Our two-stage system lever
Externí odkaz:
http://arxiv.org/abs/2011.01447
Autor:
Hu, Hu, Yang, Chao-Han Huck, Xia, Xianjun, Bai, Xue, Tang, Xin, Wang, Yajian, Niu, Shutong, Chai, Li, Li, Juanjuan, Zhu, Hongning, Bao, Feng, Zhao, Yuanjun, Siniscalchi, Sabato Marco, Wang, Yannan, Du, Jun, Lee, Chin-Hui
In this technical report, we present a joint effort of four groups, namely GT, USTC, Tencent, and UKE, to tackle Task 1 - Acoustic Scene Classification (ASC) in the DCASE 2020 Challenge. Task 1 comprises two different sub-tasks: (i) Task 1a focuses o
Externí odkaz:
http://arxiv.org/abs/2007.08389