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检索条件"机构=School of Computer and Data Engineering"
11206 条 记 录,以下是371-380 订阅
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Multiclass Classification and Defect Detection of Steel Tube Using Modified YOLO  30th
Multiclass Classification and Defect Detection of Steel Tu...
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30th International Conference on Neural Information Processing, ICONIP 2023
作者: G, Deepti Raj B, Prabadevi Gadekallu, Thippa Reddy Bhatia Khan, Surbhi Saraee, Mohammed School of Computer Science Engineering and Information Systems VIT University Vellore India Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon College of Information Science and Engineering Jiaxing University Jiaxing314001 China Department of Data Science School of Science Engineering and Environement University of Salford Manchester United Kingdom School of science engineering and environment University of Salford Salford United Kingdom
Steel tubes are widely used in hazardous high pressure environments such as petroleum, chemicals, natural gas and shale gas. Defects in steel tubes have serious negative consequences. Using deep learning object recogn... 详细信息
来源: 评论
Multicomponent Similarity Graphs for Cross-Network Node Classification
IEEE Transactions on Artificial Intelligence
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IEEE Transactions on Artificial Intelligence 2024年 第3期5卷 1411-1424页
作者: Zhang, Yuhong Shi, Congmei Li, Xinzheng Zhang, Zan Hu, Xuegang School of Computer Science and Information Engineering Hefei University of Technology Hefei230601 China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei230088 China Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Ministry of Education Hefei230009 China
Cross-network node classification aims to train a classifier for an unlabeled target network using a source network with rich labels. In applications, the degree of nodes mostly conforms to the long-tail distribution,... 详细信息
来源: 评论
Household Waste Classification Algorithms Based on Various Convolutional Neural Networks: A Review of Performance Optimization  21
Household Waste Classification Algorithms Based on Various C...
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21st International computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2024
作者: Renxiang, Huang Jia, Chen Jianping, Li School of Artificial Intelligence and Big Data Sichuan University of Arts and Science Chengdu635002 China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China
This paper reviews the research progress of deep learning-based household waste classification algorithms. It first introduces the importance of household waste classification and the application value of deep learnin... 详细信息
来源: 评论
Improving the Utility of Differentially Private SGD by Employing Wavelet Transforms
Improving the Utility of Differentially Private SGD by Emplo...
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2023 IEEE International Conference on Big data, Bigdata 2023
作者: Ranaweera, Kanishka Smith, David Nguyen, Dinh C. Pathirana, Pubudu N. Ding, Ming Rakotoarivelo, Thierry Seneviratne, Aruna Deakin University School of Engineering Australia Data61 Csiro Australia The University of Alabama in Huntsville Department of Electrical and Computer Engineering United States School of Electrical Engineering and Telecommunications Unsw Australia
Deep learning (DL) has become a powerful tool in many areas of research and industry, ranging from computer vision to natural language processing. Nonetheless, as DL models are trained on large amounts of sensitive da... 详细信息
来源: 评论
A Hybrid Deep Learning Framework for Stock Price Forecasting with Sentimental Analysis  13
A Hybrid Deep Learning Framework for Stock Price Forecasting...
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13th International Conference on System Modeling and Advancement in Research Trends, SMART 2024
作者: Banoth, Shobhan Yadala, Sucharitha Vice President-Data/Information Management Lead Engineer Citi Bank United States School of Computer Science and Engineering Vnr Vignana Jyothi Institute of Engineering & Technology Telangana Hyderabad India
Social media electronic word-of-mouth data affects stock market confidence and trading. As a result, stock market sentiment research of comments is essential for stock market forecasting. Unfortunately, English is bec... 详细信息
来源: 评论
Fast Parallel Recovery for Transactional Stream Processing on Multicores  40
Fast Parallel Recovery for Transactional Stream Processing o...
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40th IEEE International Conference on data engineering, ICDE 2024
作者: Zhao, Jianjun Liu, Haikun Zhang, Shuhao Duan, Zhuohui Liao, Xiaofei Jin, Hai Zhang, Yu School of Computer Science and Technology Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab Wuhan China School of Computer Science and Engineering Nanyang Technological University Singapore
Transactional stream processing engines (TSPEs) have gained increasing attention due to their capability of processing real-time stream applications with transactional semantics. However, TSPEs remain susceptible to s... 详细信息
来源: 评论
SSDRec: Self-Augmented Sequence Denoising for Sequential Recommendation  40
SSDRec: Self-Augmented Sequence Denoising for Sequential Rec...
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40th IEEE International Conference on data engineering, ICDE 2024
作者: Zhang, Chi Han, Qilong Chen, Rui Zhao, Xiangyu Tang, Peng Song, Hongtao College of Computer Science and Technology Harbin Engineering University China School of Data Science City University of Hong Kong Hong Kong School of Cyber Science and Technology Shandong University China
Traditional sequential recommendation methods assume that users' sequence data is clean enough to learn accurate sequence representations to reflect user preferences. In practice, users' sequences inevitably c... 详细信息
来源: 评论
GACP:graph neural networks with ARMA flters and a parallel CNN for hyperspectral image classification
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International Journal of Digital Earth 2023年 第1期16卷 1770-1800页
作者: Jing Yang Jie Sun Yaping Ren Shaobo Li Shujie Ding Jianjun Hu School of Mechanical Engineering Guizhou UniversityGuiyangPeople’s Republic of China State Key Laboratory of Public Big Data Guizhou UniversityGuiyangPeople’s Republic of China School of Intelligent Systems Science and Engineering Jinan UniversityZhuhaiPeople’s Republic of China Department of Computer Science and Engineering University of South CarolinaColumbiaSCUSA
In recent years,the use of convolutional neural networks(CNNs)and graph neural networks(GNNs)to identify hyperspectral images(HSIs)has achieved excellent results,and such methods are widely used in agricultural remote... 详细信息
来源: 评论
TROPICAL: Transformer-Based Hypergraph Learning for Camouflaged Fraudster Detection  24
TROPICAL: Transformer-Based Hypergraph Learning for Camoufla...
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24th IEEE International Conference on data Mining, ICDM 2024
作者: Haghighi, Venus Soltani, Behnaz Shabani, Nasrin Wu, Jia Zhang, Yang Yao, Lina Sheng, Quan Z. Yang, Jian School of Computing Macquarie University SydneyNSW2109 Australia School of Computer Science and Engineering University of New South Wales NSW Australia CSIRO's Data61 Australia
Graph-based fraud detection has attracted increasing attention in recent years, reflecting its growing potential in mitigating sophisticated fraudulent activities. The main objective of graph-based fraud detection is ... 详细信息
来源: 评论
Flow-Guided Deformable Alignment Network with Self-Supervision for Video Inpainting  48
Flow-Guided Deformable Alignment Network with Self-Supervisi...
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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023
作者: Wu, Zhiliang Zhang, Kang Sun, Changchang Xuan, Hanyu Yan, Yan Nanjing University of Science and Technology School of Computer Science and Engineering China Illinois Institute of Technology Department of Computer Science United States Anhui University School of Big Data and Statistics China
Video inpainting aims to utilize plausible contents to fill missing regions in the video. State-of-the-art video inpainting methods typically generate the missing contents of the target frame (current frame) by aggreg... 详细信息
来源: 评论