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检索条件"机构=Jiangsu Key Lab of Big Data and Security and Intelligent Processing"
238 条 记 录,以下是41-50 订阅
排序:
Recognition of Disaster Images Based on Self-Supervised Learning  7
Recognition of Disaster Images Based on Self-Supervised Lear...
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7th International Conference on Cloud Computing and big data Analytics, ICCCBDA 2022
作者: Wang, Linyong Wu, Ruiqi Li, Cen Zou, Zhiqiang Nanjing University of Posts and Telecommunications NanJing China College of Computer Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Big Data Security and Intelligent Processing NanJing China
Existing supervised deep learning model requires large amounts of labeled training data to learn new tasks. This is a limitation for many practical applications in disaster areas as well as in many other fields such a... 详细信息
来源: 评论
A Network Fault Prediction-Based Service Migration Approach for Unstable Mobile Edge Environment
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Wireless Communications and Mobile Computing 2023年 第1期2023卷
作者: Wang, Haiyan Tang, Weihao Luo, Jian Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China
How to perform efficient service migration in a mobile edge environment has become one of the research hotspots in the field of service computing. Most service migration approaches assume that the mobile edge network ... 详细信息
来源: 评论
Economical Electricity Supplement for Mobile Collectors in Large-Scale Multitask WSNs
Economical Electricity Supplement for Mobile Collectors in L...
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IEEE International Conference on big data and Cloud Computing (BdCloud)
作者: Xin Zhai Lijie Xu Jialei Zhang Kun Wang Jia Xu Bei Xu Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China
For large-scale multitask wireless sensor networks (LSM-WSNs), the traditional data collection mode could suffer low energy-efficiency on data transmission, since the large-scale multitask scenarios could result in mu...
来源: 评论
An Answer Summarization Scheme Based on Multilayer Attention Model
An Answer Summarization Scheme Based on Multilayer Attention...
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International Conference on Computer Supported Cooperative Work in Design
作者: Xiaolong Xu Yihao Dong Jian Song Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China
At present, deep learning technologies have been widely used in the field of natural language process, such as text summarization. In CQA, the answer summary could help users get a complete answer quickly. There are s...
来源: 评论
SSR-TA: Sequence to Sequence based expert recurrent recommendation for ticket automation
arXiv
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arXiv 2023年
作者: Cao, Chenhan Fang, Xiaoyu Luo, Bingqing Xia, Bin Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China
The ticket automation provides crucial support for the normal operation of IT software systems. An essential task of ticket automation is to assign experts to solve upcoming tickets. However, facing thousands of ticke... 详细信息
来源: 评论
Classifying Galaxy Morphologies with Few-shot Learning
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Research in Astronomy and Astrophysics 2022年 第5期22卷 9-20页
作者: Zhirui Zhang Zhiqiang Zou Nan Li Yanli Chen College of Computer Nanjing University of Posts and Telecommunications Nanjing 210023.China Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing 210023China Key Laboratory of Optical Astronomy National Astronomical ObservatoriesChinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China
The taxonomy of galaxy morphology is critical in astrophysics as the morphological properties are powerful tracers of galaxy *** the upcoming Large-scale Imaging Surveys,billions of galaxy images challenge astronomers... 详细信息
来源: 评论
Dlr: Adversarial Examples Detection and label Recovery for Deep Neural Networks
SSRN
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SSRN 2023年
作者: Han, Keji Ge, Yao Wang, Ruchuan Li, Yun Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing University of Posts and Telecommunications Jiangsu Nanjing210023 China
Deep neural networks (DNNs) are demonstrated to be vulnerable to the adversarial example crafted by the adversary to fool the target model. Adversarial training and adversarial example detection are two popular method... 详细信息
来源: 评论
Community Detection Based on Deep Network Embedding with Dual Self-supervised Training  3rd
Community Detection Based on Deep Network Embedding with Dua...
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3rd International Conference on big data and security, ICBDS 2021
作者: Chen, Yunfang Mao, Haotian Wang, Li Zhang, Wei School of Computer Science Nanjing University of Posts and Telecommunications Jiangsu Nanjing210023 China Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing University of Posts and Telecommunications Jiangsu Nanjing210023 China
We propose a community discovery method based on deep auto-encoding (DGAE_DST). Firstly, we use the pre-trained two-layer neural network and k-means algorithm to initialize the centroid vector, and then use the DNN mo... 详细信息
来源: 评论
Design Guidance for Lightweight Object Detection Models  3rd
Design Guidance for Lightweight Object Detection Models
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3rd International Conference on big data and security, ICBDS 2021
作者: Wang, Rui Wang, Xueli Chen, Yunfang Zhang, Wei School of Computer Science Nanjing University of Posts and Telecommunications Jiangsu Nanjing210023 China Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing University of Posts and Telecommunications Jiangsu Nanjing210023 China
The lightweight target detection model is deployed in an environment with limited computing power and power consumption, which is widely used in many fields. Most of the current lightweight technologies only focus on ... 详细信息
来源: 评论
Learning Disentangled Latent Factors for Individual Treatment Effect Estimation Using Variational Generative Adversarial Nets  25
Learning Disentangled Latent Factors for Individual Treatmen...
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25th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2022
作者: Bao, Qingsen Mao, Zeyong Chen, Lei Nanjing University of Posts and Telecommunications School of Computer Science Nanjing China Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing China
Estimating individual treatment effect (ITE) is a challenging task due to the need for individual potential outcomes to be learned from biased data and counterfactuals are inherently unobservable. Some researchers pro... 详细信息
来源: 评论