Zobrazeno 1 - 10
of 67
pro vyhledávání: '"Yuguang Yan"'
Autor:
Qingliang Li, Qiyun Xiao, Cheng Zhang, Jinlong Zhu, Xiao Chen, Yuguang Yan, Pingping Liu, Wei Shangguan, Zhongwang Wei, Lu Li, Wenzong Dong, Yongjiu Dai
Publikováno v:
Geoderma, Vol 449, Iss , Pp 116999- (2024)
Understanding and predicting global soil moisture (SM) is crucial for water resource management and agricultural production. While deep learning methods (DL) have shown strong performance in SM prediction, imbalances in training samples with differen
Externí odkaz:
https://doaj.org/article/7d37dc613a9447ed95ac1067373f3490
Publikováno v:
Water, Vol 16, Iss 15, p 2156 (2024)
Deep learning models possess the capacity to accurately forecast various hydrological variables, encompassing flow, temperature, and runoff, notably leveraging Long Short-Term Memory (LSTM) networks to exhibit exceptional performance in capturing lon
Externí odkaz:
https://doaj.org/article/f408b78e817b4ce79a0e465325e9cf4f
Publikováno v:
BMC Medical Imaging, Vol 21, Iss 1, Pp 1-12 (2021)
Abstract Background Chest X-rays are the most commonly available and affordable radiological examination for screening thoracic diseases. According to the domain knowledge of screening chest X-rays, the pathological information usually lay on the lun
Externí odkaz:
https://doaj.org/article/d2a479e3bf384b1395c0ac138a83fa8d
Publikováno v:
IEEE Access, Vol 7, Pp 142551-142563 (2019)
Domain adaptation aims at extracting knowledge from an auxiliary source domain to assist the learning task in a target domain. When the data distribution of the target domain is different from that of the source domain, the direct use of source data
Externí odkaz:
https://doaj.org/article/b6f9f779fe2b4027a6ecee1f1192284e
Publikováno v:
International Journal of Advanced Robotic Systems, Vol 12 (2015)
Affordances define the relationships between the robot and environment, in terms of actions that the robot is able to perform. Prior work is mainly about predicting the possibility of a reactive action, and the object's affordance is invariable. Howe
Externí odkaz:
https://doaj.org/article/9ee74c2a90c24f7bae1ce102b02a25f3
Autor:
Chang’an Yi, Haotian Chen, Yonghui Xu, Huanhuan Chen, Yong Liu, Haishu Tan, Yuguang Yan, Han Yu
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. :1-15
Autor:
Qingyao Wu, Yuzhong Ye, Hanrui Wu, Liu Dapeng, Min Lu, Yuguang Yan, Bi Chaoyang, Michael K. Ng
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 34:5536-5551
Domain adaptation aims at extracting knowledge from auxiliary source domains to assist the learning task in a target domain. In classification problems, since the distributions of the source and target domains are different, directly using source dat
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. :1-12
Sequential recommendation aims to choose the most suitable items for a user at a specific timestamp given historical behaviors. Existing methods usually model the user behavior sequence based on transition-based methods such as Markov chain. However,
Publikováno v:
IEEE transactions on pattern analysis and machine intelligence.
In many practical data sets, such as co-citation and co-authorship, relationships across the samples are more complex than pair-wise. Hypergraphs provide a flexible and natural representation for such complex correlations and thus obtain increasing a
Publikováno v:
IEEE Transactions on Image Processing. 30:6364-6376
Heterogeneous domain adaptation (HDA) is a challenging problem because of the different feature representations in the source and target domains. Most HDA methods search for mapping matrices from the source and target domains to discover latent featu