Zobrazeno 1 - 10
of 1 680
pro vyhledávání: '"Wu Yanan"'
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
Based on ELAN multimodal discourse analysis software, this paper constructs a multimodal Russian translation model based on the machine translation model with visual grammar and multimodal discourse analysis as the theoretical basis. To address the i
Externí odkaz:
https://doaj.org/article/03aaa2dd3481485f8995880528772926
Autor:
Wu Yanan
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
In this paper, we model the knowledge graph by constructing the new mechanism of tax collection and administration under the empowerment of IoT technology and give the knowledge subgraph and operation of the new mechanism of tax collection and admini
Externí odkaz:
https://doaj.org/article/4bd53fcfeceb42a6991acdb2b5370d8c
Autor:
Tang Guangfu, Zhou Jing, Pang Hui, Lin Junjie, Fan Zheng, Wu Yanan, He Zhiyuan, Ma Shicong, Xue Feng, Zhou Baorong
Publikováno v:
中国工程科学, Vol 25, Iss 2, Pp 79-88 (2023)
The construction of a new electric power system is the key path to achieve the carbon peaking and carbon neutrality goals and ensure energy transition security. As the largest man-made system that is complex and highly nonlinear, the electric power s
Externí odkaz:
https://doaj.org/article/cba1bd9b4cb942c4a1f3c05825697e37
Publikováno v:
Intelligent Surgery, Vol 2, Iss , Pp 14-21 (2022)
Holographic navigation guidance technology mainly refers to the intraoperative holography navigation using a mixed-reality wearable computer, which can provide more probabilities to accurately remove the tumors and preserve more normal tissues. We re
Externí odkaz:
https://doaj.org/article/3553fdd5220149e3bb74fde9e4f996ae
Autor:
Liu, Jiaheng, Deng, Ken, Liu, Congnan, Yang, Jian, Liu, Shukai, Zhu, He, Zhao, Peng, Chai, Linzheng, Wu, Yanan, Jin, Ke, Zhang, Ge, Wang, Zekun, Zhang, Guoan, Xiang, Bangyu, Su, Wenbo, Zheng, Bo
Repository-level code completion has drawn great attention in software engineering, and several benchmark datasets have been introduced. However, existing repository-level code completion benchmarks usually focus on a limited number of languages (<5)
Externí odkaz:
http://arxiv.org/abs/2410.21157
Glioma, a common and deadly brain tumor, requires early diagnosis for improved prognosis. However, low-quality Magnetic Resonance Imaging (MRI) technology in Sub-Saharan Africa (SSA) hinders accurate diagnosis. This paper presents our work in the Bra
Externí odkaz:
http://arxiv.org/abs/2410.18698
Incremental Few-Shot Semantic Segmentation (iFSS) tackles a task that requires a model to continually expand its segmentation capability on novel classes using only a few annotated examples. Typical incremental approaches encounter a challenge that t
Externí odkaz:
http://arxiv.org/abs/2410.13094
Autor:
Wang, Pei, Wu, Yanan, Wang, Zekun, Liu, Jiaheng, Song, Xiaoshuai, Peng, Zhongyuan, Deng, Ken, Zhang, Chenchen, Wang, Jiakai, Peng, Junran, Zhang, Ge, Guo, Hangyu, Zhang, Zhaoxiang, Su, Wenbo, Zheng, Bo
Large Language Models (LLMs) have displayed massive improvements in reasoning and decision-making skills and can hold natural conversations with users. Recently, many tool-use benchmark datasets have been proposed. However, existing datasets have the
Externí odkaz:
http://arxiv.org/abs/2410.11710
Autor:
Liu, Jiaheng, Zhang, Chenchen, Guo, Jinyang, Zhang, Yuanxing, Que, Haoran, Deng, Ken, Bai, Zhiqi, Liu, Jie, Zhang, Ge, Wang, Jiakai, Wu, Yanan, Liu, Congnan, Su, Wenbo, Wang, Jiamang, Qu, Lin, Zheng, Bo
Despite the advanced intelligence abilities of large language models (LLMs) in various applications, they still face significant computational and storage demands. Knowledge Distillation (KD) has emerged as an effective strategy to improve the perfor
Externí odkaz:
http://arxiv.org/abs/2407.16154
Autor:
Wang, Ziqiang, Chi, Zhixiang, Wu, Yanan, Gu, Li, Liu, Zhi, Plataniotis, Konstantinos, Wang, Yang
Given a model trained on source data, Test-Time Adaptation (TTA) enables adaptation and inference in test data streams with domain shifts from the source. Current methods predominantly optimize the model for each incoming test data batch using self-t
Externí odkaz:
http://arxiv.org/abs/2407.12128