Zobrazeno 1 - 10
of 136
pro vyhledávání: '"Xie, Dongliang"'
Publikováno v:
In Journal of Physics and Chemistry of Solids October 2024 193
Autor:
Xie, Dongliang, Kuang, Yi, Yuan, Bingnan, Zhang, Yunlong, Ye, Chenyu, Guo, Yuyi, Qiu, Hua, Ren, Juanna, Alshammari, Saud O., Alshammari, Qamar A., El-Bahy, Zeinhom M., Zhao, Kui, Guo, Zhanhu, Rao, Qingqing, Yang, Shengxiang
Publikováno v:
In Journal of Materials Science & Technology 10 March 2025 211:159-170
State-of-the-art techniques in Generative Adversarial Networks (GANs) have shown remarkable success in image-to-image translation from peer domain X to domain Y using paired image data. However, obtaining abundant paired data is a non-trivial and exp
Externí odkaz:
http://arxiv.org/abs/2008.11882
Publikováno v:
ACM Multimedia 2020
Outfit recommendation requires the answers of some challenging outfit compatibility questions such as 'Which pair of boots and school bag go well with my jeans and sweater?'. It is more complicated than conventional similarity search, and needs to co
Externí odkaz:
http://arxiv.org/abs/2008.08189
Autor:
Yang, Xuewen, Zhang, Heming, Jin, Di, Liu, Yingru, Wu, Chi-Hao, Tan, Jianchao, Xie, Dongliang, Wang, Jue, Wang, Xin
Generating accurate descriptions for online fashion items is important not only for enhancing customers' shopping experiences, but also for the increase of online sales. Besides the need of correctly presenting the attributes of items, the expression
Externí odkaz:
http://arxiv.org/abs/2008.02693
Publikováno v:
In Signal Processing: Image Communication September 2023 117
Autor:
Liu, Yingru, Yang, Xuewen, Xie, Dongliang, Wang, Xin, Shen, Li, Huang, Haozhi, Balasubramanian, Niranjan
Multi-task learning (MTL) is a common paradigm that seeks to improve the generalization performance of task learning by training related tasks simultaneously. However, it is still a challenging problem to search the flexible and accurate architecture
Externí odkaz:
http://arxiv.org/abs/1911.08065
Autor:
Wu, Juai, Zhang, Mengying, Xu, Tianheng, Gu, Duan, Xie, Dongliang, Zhang, Tengfei, Hu, Honglin, Zhou, Ting
Publikováno v:
In Renewable and Sustainable Energy Reviews August 2023 182
Learning target side syntactic structure has been shown to improve Neural Machine Translation (NMT). However, incorporating syntax through latent variables introduces additional complexity in inference, as the models need to marginalize over the late
Externí odkaz:
http://arxiv.org/abs/1908.11782
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