Zobrazeno 1 - 10
of 871
pro vyhledávání: '"LI Xiyao"'
Autor:
LI Sanzhong, SUO Yanhui, ZHOU Jie, WANG Guangzeng, LI Xiyao, JIANG Zhaoxia, LIU Jinping, LIU Lijun, LIU Yongjiang, ZHAN Huawang, JIANG Suhua, CHENG Haohao, WANG Pengcheng, ZHU Junjiang, DAI Liming, DONG Hao, LIU Lin, GUO Xiaoyu
Publikováno v:
Dizhi lixue xuebao, Vol 28, Iss 5, Pp 683-704 (2022)
The northern South China Sea continental margin is the key or critical segment of the Ocean-Continent Connection Zone (OCCZ) of the Great South China Block, the junction between the Tethyan and the (Paleo-) Pacific dynamic systems, and the interactio
Externí odkaz:
https://doaj.org/article/5c67c521add5459383c61786d0b8b2f1
Publikováno v:
智慧农业, Vol 4, Iss 1, Pp 1-16 (2022)
Diseases and pests are main stresses to crop production. It is necessary to accurately and quickly monitor and control the stresses dynamically, so as to ensure the food security and the quality and safety of agricultural products, protect the ecolog
Externí odkaz:
https://doaj.org/article/638f0dd8a18f46e48f61f30893e02bb7
Autor:
Deng, Xiuqi, Xu, Lu, Li, Xiyao, Yu, Jinkai, Xue, Erpeng, Wang, Zhongyuan, Zhang, Di, Liu, Zhaojie, Zhou, Guorui, Song, Yang, Mou, Na, Jiang, Shen, Li, Han
Traditional recommender systems heavily rely on ID features, which often encounter challenges related to cold-start and generalization. Modeling pre-extracted content features can mitigate these issues, but is still a suboptimal solution due to the d
Externí odkaz:
http://arxiv.org/abs/2404.06078
Current Large Language Model-based agents reason within an exploration-evaluation framework, navigating problem-solving processes in a tree-like manner. However, these methods often neglect successful reasoning trajectories once a problem is resolved
Externí odkaz:
http://arxiv.org/abs/2312.17445
Autor:
Fang, Kaipeng, Song, Jingkuan, Gao, Lianli, Zeng, Pengpeng, Cheng, Zhi-Qi, Li, Xiyao, Shen, Heng Tao
The goal of Universal Cross-Domain Retrieval (UCDR) is to achieve robust performance in generalized test scenarios, wherein data may belong to strictly unknown domains and categories during training. Recently, pre-trained models with prompt tuning ha
Externí odkaz:
http://arxiv.org/abs/2312.12478
Knowledge Graph Completion (KGC) aims to conduct reasoning on the facts within knowledge graphs and automatically infer missing links. Existing methods can mainly be categorized into structure-based or description-based. On the one hand, structure-ba
Externí odkaz:
http://arxiv.org/abs/2308.08204
In this work we develop a novel approach using deep neural networks to reconstruct the conductivity distribution in elliptic problems from one measurement of the solution over the whole domain. The approach is based on a mixed reformulation of the go
Externí odkaz:
http://arxiv.org/abs/2303.16454
Fashion image retrieval task aims to search relevant clothing items of a query image from the gallery. The previous recipes focus on designing different distance-based loss functions, pulling relevant pairs to be close and pushing irrelevant images a
Externí odkaz:
http://arxiv.org/abs/2302.08902
Conductivity imaging represents one of the most important tasks in medical imaging. In this work we develop a neural network based reconstruction technique for imaging the conductivity from the magnitude of the internal current density. It is achieve
Externí odkaz:
http://arxiv.org/abs/2204.02441
In Domain Generalization (DG) tasks, models are trained by using only training data from the source domains to achieve generalization on an unseen target domain, this will suffer from the distribution shift problem. So it's important to learn a class
Externí odkaz:
http://arxiv.org/abs/2203.17067