Zobrazeno 1 - 10
of 415
pro vyhledávání: '"MA Yufeng"'
Publikováno v:
Polish Journal of Chemical Technology, Vol 20, Iss 2, Pp 47-53 (2018)
A novel 9, 10-dihydro-9-oxa-10-phosphaphenanthrene-10-oxide (DOPO) graft γ-amino propyl triethoxy silane (KH550) was synthesized and introduced on the surface of wood fiber. Finally DOPO-g-KH550 treated wood fiber (DKTWF) was used to prepare DKTWF c
Externí odkaz:
https://doaj.org/article/f7ab81a6e251407eb91e35336f0d4b36
Publikováno v:
Polish Journal of Chemical Technology, Vol 19, Iss 4, Pp 116-121 (2017)
Eucalyptus fibers were modified with N-β(aminoethyl)-γ-aminopropyl trimethoxy silane to research the fiber surface’s changes and the influence of the treatment on the mechanical properties, flame resistance, thermal conductivity and microstructur
Externí odkaz:
https://doaj.org/article/490d7b908b5a41eaa7e800ae38a3ff1f
Autor:
Wang, Longyue, Tu, Zhaopeng, Gu, Yan, Liu, Siyou, Yu, Dian, Ma, Qingsong, Lyu, Chenyang, Zhou, Liting, Liu, Chao-Hong, Ma, Yufeng, Chen, Weiyu, Graham, Yvette, Webber, Bonnie, Koehn, Philipp, Way, Andy, Yuan, Yulin, Shi, Shuming
Translating literary works has perennially stood as an elusive dream in machine translation (MT), a journey steeped in intricate challenges. To foster progress in this domain, we hold a new shared task at WMT 2023, the first edition of the Discourse-
Externí odkaz:
http://arxiv.org/abs/2311.03127
Autor:
Zheng, Yu, Peng, Jinghan, Zhao, Miao, Ma, Yufeng, Liu, Min, Ma, Xinyue, Liang, Tianyu, Kong, Tianlong, He, Liang, Xu, Minqiang
This paper presents the system description of the THUEE team for the NIST 2020 Speaker Recognition Evaluation (SRE) conversational telephone speech (CTS) challenge. The subsystems including ResNet74, ResNet152, and RepVGG-B2 are developed as speaker
Externí odkaz:
http://arxiv.org/abs/2210.06111
Publikováno v:
In Results in Physics November 2024 66
Publikováno v:
In Advanced Engineering Informatics October 2024 62 Part A
Publikováno v:
In Information Sciences September 2024 679
Multi-branch convolutional neural network architecture has raised lots of attention in speaker verification since the aggregation of multiple parallel branches can significantly improve performance. However, this design is not efficient enough during
Externí odkaz:
http://arxiv.org/abs/2110.09720
This paper describes the multi-query multi-head attention (MQMHA) pooling and inter-topK penalty methods which were first proposed in our submitted system description for VoxCeleb speaker recognition challenge (VoxSRC) 2021. Most multi-head attention
Externí odkaz:
http://arxiv.org/abs/2110.05042
Most recent speaker verification systems are based on extracting speaker embeddings using a deep neural network. The pooling layer in the network aims to aggregate frame-level features extracted by the backbone. In this paper, we propose a new transf
Externí odkaz:
http://arxiv.org/abs/2110.04692