Zobrazeno 1 - 10
of 319
pro vyhledávání: '"Lu Guojun"'
Autor:
Yao, Wang, Lu, Guojun, Zhao, Hongwei, Huang, Dongbin, Bai, Bihai, Huang, Nihui, Yu, Mingxin, Cao, Chunyan, Li, Yuechan, Xie, An
Publikováno v:
In Optical Materials November 2024 157 Part 1
Autor:
Bai, Bihai, Huang, Nihui, Lu, Guojun, Yao, Wang, Zhao, Hongwei, Yu, Mingxin, Cao, Chunyan, Li, Yuechan, Xie, An
Publikováno v:
In Ceramics International 15 October 2024 50(20) Part B:38952-38962
Publikováno v:
In Intelligent Systems with Applications September 2024 23
Autor:
Wan, Chenxiao, Ju, Xiaoyan, Xu, Dandan, Ou, Jinzhao, Zhu, Meng, Lu, Guojun, Li, Kejia, Jiang, Wei, Li, Chunyan, Hu, Xiaohua, Tian, Ye, Niu, Zhongwei
Publikováno v:
In Acta Biomaterialia 1 September 2024 185:215-225
Deep convolutional networks are vulnerable to image translation or shift, partly due to common down-sampling layers, e.g., max-pooling and strided convolution. These operations violate the Nyquist sampling rate and cause aliasing. The textbook soluti
Externí odkaz:
http://arxiv.org/abs/2110.00899
Convolutional Neural Networks (CNNs) are commonly designed for closed set arrangements, where test instances only belong to some "Known Known" (KK) classes used in training. As such, they predict a class label for a test sample based on the distribut
Externí odkaz:
http://arxiv.org/abs/2109.12756
Autor:
Li, Kejia, Ju, Xiaoyan, Li, Xiangli, Lu, Guojun, Ou, Jinzhao, Xu, Dandan, Wan, Chenxiao, Zhu, Meng, Du, Chuanchao, Tian, Ye, Niu, Zhongwei
Publikováno v:
In Chemical Engineering Journal 1 June 2024 489
Autor:
Huang, Nihui, Lu, Guojun, Bai, Bihai, Zhao, Hongwei, Yao, Wang, Cao, Chunyan, Li, Yuechan, Xie, An
Publikováno v:
In Journal of Luminescence May 2024 269
Attention is a very popular and effective mechanism in artificial neural network-based sequence-to-sequence models. In this survey paper, a comprehensive review of the different attention models used in developing automatic speech recognition systems
Externí odkaz:
http://arxiv.org/abs/2102.07259
Publikováno v:
Pattern Recognition, 2021
Embedding learning (EL) and feature synthesizing (FS) are two of the popular categories of fine-grained GZSL methods. EL or FS using global features cannot discriminate fine details in the absence of local features. On the other hand, EL or FS method
Externí odkaz:
http://arxiv.org/abs/2101.02141