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检索条件"机构=Computer and System Technology Laboratory"
5137 条 记 录,以下是251-260 订阅
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Vulnerability Detection Based on Pre-trained Code Language Model and Convolutional Neural Network  36
Vulnerability Detection Based on Pre-trained Code Language M...
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36th International Conference on Software Engineering and Knowledge Engineering, SEKE 2024
作者: Liao, Tingfeng Lu, Lu Liang, Zhihong Suo, Siliang School of Computer Science and Engineering South China University of Technology Guangzhou China Pazhou Laboratory Guangzhou China Pengcheng Laboratory Shenzhen China Electric Power Research Institute CSG Guangzhou China Guangdong Provincial Key Laboratory of Power System Network Security Guangzhou China
Software vulnerabilities damage the reliability of software systems. Recently, many methods based on deep learning have been proposed for vulnerability detection by learning features from code sequences or various pro... 详细信息
来源: 评论
Defect Screening on Nuclear Power Plant Concrete Structures: A Two-staged Method Based on Contrastive Representation Learning  8
Defect Screening on Nuclear Power Plant Concrete Structures:...
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8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023
作者: Huang, Wenlian Zhu, Guanming Huang, Qiang Chen, Zhuangzhuang Chen, Jie Li, Jianqiang College of Computer Science and Software Engineering Shenzhen University Shenzhen China Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen China
Intelligent defect detection methods are important for the surface of the containment of nuclear power plants and face many challenges in the field of computer vision. Due to the irregular shapes and large variation o... 详细信息
来源: 评论
Focused Feature Enhancement and Multi-scale Feature Fusion for Road Defect Detection
Focused Feature Enhancement and Multi-scale Feature Fusion f...
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International Conference on computer Supported Cooperative Work in Design
作者: Yanan Li Fayu Wang Hongtao Chen Xinge Li Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin China
Given the characteristics of road defect detection, such as the small proportion of defective targets in defective images, the large scale difference of different types of defects, and the complex background environme... 详细信息
来源: 评论
HiCoCS: High Concurrency Cross-Sharding on Permissioned Blockchains
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IEEE Transactions on computers 2025年 第7期74卷 2168-2182页
作者: Yang, Lingxiao Dong, Xuewen Wan, Zhiguo Lu, Di Zhang, Yushu Shen, Yulong Xidian University School of Computer Science and Technology Xi’an710071 China Ministry of Education Engineering Research Center of Blockchain Technology Application and Evaluation Xi’an710071 China Shaanxi Key Laboratory of Blockchain and Secure Computing Xi’an710071 China Zhejiang Lab Zhejiang Hangzhou311121 China Shaanxi Key Laboratory of Network and System Security Xi’an710071 China Jiangxi University of Finance and Economics School of Computing and Artificial Intelligence Nanchang330013 China
As the foundation of the Web3 trust system, blockchain technology faces increasing demands for scalability. Sharding emerges as a promising solution, but it struggles to handle highly concurrent cross-shard transactio... 详细信息
来源: 评论
Surpass Teacher: Enlightenment Structured Knowledge Distillation of Transformer
Surpass Teacher: Enlightenment Structured Knowledge Distilla...
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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023
作者: Yang, Ran Deng, Chunhua School of Computer Science and Technology Wuhan University of Science and Technology Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan430065 China
It is difficult to train a trustworthy transformer model on a small image classification dataset. This research proposes a sophisticated structured knowledge distillation algorithm that uses CNNs as Transformer's ...
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A Composite Decomposition Method for Large-Scale Global Optimization
IEEE Transactions on Artificial Intelligence
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IEEE Transactions on Artificial Intelligence 2024年 第12期5卷 6304-6319页
作者: Tian, Maojiang Chen, Minyang Du, Wei Tang, Yang Jin, Yaochu Yen, Gary G. Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen518055 China East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China East China University of Science and Technology Engineering Research Center of Process System Engineering Ministry of Education Shanghai200237 China Westlake University School of Engineering Hangzhou310030 China Oklahoma State University School of Electrical and Computer Engineering StillwaterOK74048 United States
Cooperative coevolution (CC) algorithms, based on the divide-and-conquer strategy, have emerged as the predominant approach to solving large-scale global optimization (LSGO) problems. The efficiency and accuracy of th... 详细信息
来源: 评论
Research on Object Detection Optimization Method for Complex Traffic Environment
Research on Object Detection Optimization Method for Complex...
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International Conference on computer Supported Cooperative Work in Design
作者: Tong Wang Fayu Wang Xinge Li Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin China
In complex and ever-changing traffic environments, target detection tasks require extremely high accuracy and efficiency. However, current methods still have obvious limitations in their ability to focus on key areas ... 详细信息
来源: 评论
Game Learning-Based Target Allocation of the UAV Confrontation system
Game Learning-Based Target Allocation of the UAV Confronta...
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International Conference on Guidance, Navigation and Control, ICGNC 2024
作者: Hu, Yaxu Zhang, Yanling Xiao, Feng Key Laboratory of Intelligent Bionic Unmanned Systems School of Intelligence Science and Technology University of Science and Technology Beijing Beijing100083 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing102206 China
Previous studies on the UAV swarm air combat decision-making problem lack consideration of uncertainty, intense confrontation, and high dynamics of aerial combat scenarios. This paper delves into the target allocation... 详细信息
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Data quantity governance for machine learning in materials science
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National Science Review 2023年 第7期10卷 234-250页
作者: Yue Liu Zhengwei Yang Xinxin Zou Shuchang Ma Dahui Liu Maxim Avdeev Siqi Shi School of Computer Engineering and Science Shanghai University Shanghai Engineering Research Center of Intelligent Computing System Australian Nuclear Science and Technology Organisation School of Chemistry The University of Sydney State Key Laboratory of Advanced Special Steel School of Materials Science and Engineering Shanghai University Materials Genome Institute Shanghai University
Data-driven machine learning(ML) is widely employed in the analysis of materials structure-activity relationships,performance optimization and materials design due to its superior ability to reveal latent data pattern... 详细信息
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Joint DNN Partition and Thread Allocation Optimization for Energy-Harvesting MEC systems
Joint DNN Partition and Thread Allocation Optimization for E...
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2025 Design, Automation and Test in Europe Conference, DATE 2025
作者: Shi, Yizhou Li, Liying Zeng, Yue Cong, Peijin Zhou, Junlong Nanjing University National Key Laboratory for Novel Software Technology Nanjing210023 China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China Southeast University National Mobile Communications Research Laboratory Nanjing211111 China Key Laboratory of Embedded System and Service Computing Tongji University Ministry of Education Shanghai201804 China
Deep neural networks (DNNs) have demonstrated exceptional performance, leading to diverse applications across various mobile devices (MDs). Considering factors like portability and environmental sustainability, an inc... 详细信息
来源: 评论