Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Chunli Lv"'
Autor:
Shutian Zhou, Zizhe Zhou, Chenxi Wang, Yuzhe Liang, Liangyu Wang, Jiahe Zhang, Jinming Zhang, Chunli Lv
Publikováno v:
Applied Sciences, Vol 14, Iss 15, p 6824 (2024)
This paper introduces a user-centered data privacy protection framework utilizing large language models (LLMs) and user attention mechanisms, which are tailored to address urgent privacy concerns in sensitive data processing domains like financial co
Externí odkaz:
https://doaj.org/article/c8fe1a8d867c4fbeabc7805741f3b6d2
Autor:
Bingyuan Han, Peiyan Duan, Chengcheng Zhou, Xiaotong Su, Ziyan Yang, Shutian Zhou, Mengxue Ji, Yucen Xie, Jianjun Chen, Chunli Lv
Publikováno v:
Plants, Vol 13, Iss 12, p 1681 (2024)
In this study, an advanced method for apricot tree disease detection is proposed that integrates deep learning technologies with various data augmentation strategies to significantly enhance the accuracy and efficiency of disease detection. A compreh
Externí odkaz:
https://doaj.org/article/8b5e4fedc1f7404a83be7417334cd577
Autor:
Huairong Huo, Wanxin Guo, Ruining Yang, Xuran Liu, Jingyi Xue, Qingmiao Peng, Yiwei Deng, Xinyi Sun, Chunli Lv
Publikováno v:
Systems, Vol 12, Iss 5, p 171 (2024)
In this research, an innovative state space-based Transformer model is proposed to address the challenges of complex system prediction tasks. By integrating state space theory, the model aims to enhance the capability to capture dynamic changes in co
Externí odkaz:
https://doaj.org/article/d08d22845af3485099f1a59ef8cbb73b
Autor:
Yuzhe Bai, Min Sun, Liman Zhang, Yinong Wang, Sihan Liu, Yanqiu Liu, Jingling Tan, Yingqiu Yang, Chunli Lv
Publikováno v:
Applied Sciences, Vol 14, Iss 9, p 3829 (2024)
In this study, we propose a novel method for detecting cyberattack behaviors by leveraging the combined strengths of large language models and a synchronized attention mechanism. Extensive experiments conducted on diverse datasets, including server l
Externí odkaz:
https://doaj.org/article/3ad61d96cffe4125930b1e871fe1a582
Autor:
Yuchun Lu, Xiaoyi Lu, Liping Zheng, Min Sun, Siyu Chen, Baiyan Chen, Tong Wang, Jiming Yang, Chunli Lv
Publikováno v:
Plants, Vol 13, Iss 7, p 972 (2024)
In this study, an innovative approach based on multimodal data and the transformer model was proposed to address challenges in agricultural disease detection and question-answering systems. This method effectively integrates image, text, and sensor d
Externí odkaz:
https://doaj.org/article/5d74c7c1a3f141a6a4cb7bd240b299ed
Autor:
Jianye Zeng, Dandan Chen, Chunli Lv, Kening Qin, Qin Zhou, Na Pu, Shanshan Song, Xiaomin Wang
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-11 (2022)
Abstract Polygonum chinense Linn. (Polygonum chinense L.) is one of the main raw materials of Chinese patent medicines such as Guangdong herbal tea. The increasing antibiotic resistance of S. aureus and the biofilm poses a serious health threat to hu
Externí odkaz:
https://doaj.org/article/3d91f639144c4730af3a11d40050bd50
Autor:
Xinyue Wang, Weifan Lin, Weiting Zhang, Yiwen Huang, Zeyu Li, Qian Liu, Xinze Yang, Yifan Yao, Chunli Lv
Publikováno v:
Applied Sciences, Vol 14, Iss 4, p 1386 (2024)
In this paper, the Merkle-Transformer model is introduced as an innovative approach designed for financial data processing, which combines the data integrity verification mechanism of Merkle trees with the data processing capabilities of the Transfor
Externí odkaz:
https://doaj.org/article/000138bec97f4c7f85e7acf74048bc68
Autor:
Hao An, Ruotong Ma, Yuhan Yan, Tailai Chen, Yuchen Zhao, Pan Li, Jifeng Li, Xinyue Wang, Dongchen Fan, Chunli Lv
Publikováno v:
Applied Sciences, Vol 14, Iss 1, p 460 (2024)
This paper aims to address the increasingly severe security threats in financial systems by proposing a novel financial attack detection model, Finsformer. This model integrates the advanced Transformer architecture with the innovative cluster-attent
Externí odkaz:
https://doaj.org/article/6f610855dc8a43359050148c997d64fb
Autor:
Lexin Zhang, Changxiang Li, Qi Hu, Jingjing Lang, Sirui Huang, Linyue Hu, Jingwen Leng, Qiuhan Chen, Chunli Lv
Publikováno v:
Applied Sciences, Vol 13, Iss 24, p 13146 (2023)
In response to the challenges of personal privacy protection in the dialogue models of the information era, this study introduces an innovative privacy-preserving dialogue model framework. This framework seamlessly incorporates Fully Homomorphic Encr
Externí odkaz:
https://doaj.org/article/778a3f8fd9184295a8c38e709cfeb028
Publikováno v:
Information, Vol 14, Iss 9, p 499 (2023)
This research primarily explores the application of Natural Language Processing (NLP) technology in precision financial fraud detection, with a particular focus on the implementation and optimization of the FinChain-BERT model. Firstly, the FinChain-
Externí odkaz:
https://doaj.org/article/2a597bfcd7e2458db39f30436e1bd7fe