Výsledky vyhledávání - "Xingxuan Zhang"

Regulatory Instruments for Fair Personalized Pricing

Autor: Renzhe Xu, Xingxuan Zhang, Peng Cui, Bo Li, Zheyan Shen, Jiazheng Xu

Publikováno v: Proceedings of the ACM Web Conference 2022.

Personalized pricing is a business strategy to charge different prices to individual consumers based on their characteristics and behaviors. It has become common practice in many industries nowadays due to the availability of a growing amount of high

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::606fa2c1752c256fb1961f5b2e1e37d9
https://doi.org/10.1145/3485447.3512046

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Towards Unsupervised Domain Generalization

Autor: Xingxuan Zhang, Linjun Zhou, Renzhe Xu, Peng Cui, Zheyan Shen, Haoxin Liu

Domain generalization (DG) aims to help models trained on a set of source domains generalize better on unseen target domains. The performances of current DG methods largely rely on sufficient labeled data, which are usually costly or unavailable, how

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6204d562ef9d013a0e06a9123c8e3706
http://arxiv.org/abs/2107.06219

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Deep Stable Learning for Out-Of-Distribution Generalization

Autor: Linjun Zhou, Yue He, Zheyan Shen, Xingxuan Zhang, Renzhe Xu, Peng Cui

Publikováno v: CVPR

Approaches based on deep neural networks have achieved striking performance when testing data and training data share similar distribution, but can significantly fail otherwise. Therefore, eliminating the impact of distribution shifts between trainin

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::03b54cb515def5cd421b764f9dc30571

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Speaker-Independent Lipreading With Limited Data

Autor: Xingxuan Zhang, Chen-Zhao Yang, Yun Zhu, Shilin Wang

Publikováno v: ICIP

Recent researches have demonstrated that with a huge annotated training dataset, some sophisticated automatic lipreading methods perform even better than a professional human lip reader. However, when the training set is limited, i.e. containing a fe

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2a1e3a43e6fca73042f8842182705594
https://doi.org/10.1109/icip40778.2020.9190780

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Spatio-Temporal Fusion Based Convolutional Sequence Learning for Lip Reading

Autor: Feng Cheng, Xingxuan Zhang, Wang Shi-lin

Publikováno v: ICCV

Current state-of-the-art approaches for lip reading are based on sequence-to-sequence architectures that are designed for natural machine translation and audio speech recognition. Hence, these methods do not fully exploit the characteristics of the l

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5723aa864f42ab7f39a0698913677fde
https://doi.org/10.1109/iccv.2019.00080

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3D Convolutional Neural Networks Based Speaker Identification and Authentication

Autor: Gongshen Liu, Jianguo Liao, Shilin Wang, Xingxuan Zhang

Publikováno v: ICIP

Research shows that human lips can be used as a new kind of biometrics in personal identification and authentication. In this letter, a novel end-to-end method based on 3D convolutional neural network (3DCNN) is proposed to extract discriminative spa

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ce293f4bc4c7e7b21e59f83973c9902a
https://doi.org/10.1109/icip.2018.8451204

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