Zobrazeno 1 - 10
of 555
pro vyhledávání: '"TANG Yongqiang"'
Publikováno v:
Youqi dizhi yu caishoulu, Vol 31, Iss 3, Pp 156-164 (2024)
Emulsification is one of the main mechanisms of chemical flooding to enhance oil recovery in heavy oil reservoirs. The emulsification of heavy oil in porous media is closely related to reservoir temperature and oil-displacing agent concentration. The
Externí odkaz:
https://doaj.org/article/1b2f32439ddb4b788a490ecc3ed1d3f7
Different from the traditional semi-supervised learning paradigm that is constrained by the close-world assumption, Generalized Category Discovery (GCD) presumes that the unlabeled dataset contains new categories not appearing in the labeled set, and
Externí odkaz:
http://arxiv.org/abs/2410.21705
Large language models (LLMs) show excellent performance in difficult tasks, but they often require massive memories and computational resources. How to reduce the parameter scale of LLMs has become research hotspots. In this study, we make an importa
Externí odkaz:
http://arxiv.org/abs/2404.09695
Self-supervised skeleton-based action recognition enjoys a rapid growth along with the development of contrastive learning. The existing methods rely on imposing invariance to augmentations of 3D skeleton within a single data stream, which merely lev
Externí odkaz:
http://arxiv.org/abs/2305.02324
Domain adaptation manages to transfer the knowledge of well-labeled source data to unlabeled target data. Many recent efforts focus on improving the prediction accuracy of target pseudo-labels to reduce conditional distribution shift. In this paper,
Externí odkaz:
http://arxiv.org/abs/2302.08710
As a recent noticeable topic, domain generalization aims to learn a generalizable model on multiple source domains, which is expected to perform well on unseen test domains. Great efforts have been made to learn domain-invariant features by aligning
Externí odkaz:
http://arxiv.org/abs/2210.04155
Domain generalization (DG) aims to learn a model on several source domains, hoping that the model can generalize well to unseen target domains. The distribution shift between domains contains the covariate shift and conditional shift, both of which t
Externí odkaz:
http://arxiv.org/abs/2209.08253
Temporal Action Localization (TAL) aims to predict both action category and temporal boundary of action instances in untrimmed videos, i.e., start and end time. Fully-supervised solutions are usually adopted in most existing works, and proven to be e
Externí odkaz:
http://arxiv.org/abs/2208.14856
In group activity recognition, hierarchical framework is widely adopted to represent the relationships between individuals and their corresponding group, and has achieved promising performance. However, the existing methods simply employed max/averag
Externí odkaz:
http://arxiv.org/abs/2208.14847
Multi-view clustering has attracted much attention thanks to the capacity of multi-source information integration. Although numerous advanced methods have been proposed in past decades, most of them generally overlook the significance of weakly-super
Externí odkaz:
http://arxiv.org/abs/2206.04949