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检索条件"机构=CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology"
915 条 记 录,以下是511-520 订阅
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Design and Application of a Portable Sleep Inertia Detection System Based on EEG Signals
Design and Application of a Portable Sleep Inertia Detection...
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2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021
作者: Cui, Yunzhi Tian, Fuze Zhao, Qinglin Hu, Bin Lanzhou University Gansu Provincial Key Laboratory of Wearable Computing School of Information Science and Engineering Lanzhou China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai Institutes for Biological Sciences Chinese Academy of Sciences China Jt. Res. Ctr. for Cogn. Neurosensor Technology of Lanzhou University and Institute of Semiconductors Chinese Academy of Sciences China Ministry of Education Lanzhou China
Sleep inertia is a transitional state from sleep to wakefulness, accompanied by groggy feelings and cognitive impairment. Previous research on sleep inertia mainly used expensive and cumbersome equipment, and the anal... 详细信息
来源: 评论
UJN-Land: A Large-Scale High-Resolution Parcel of Land of Multi-temporal dataset with CNN Based Semantic Segmentation Analysis  7th
UJN-Land: A Large-Scale High-Resolution Parcel of Land of Mu...
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7th International Conference on Life System Modeling and Simulation, LSMS 2021, and the 7th International Conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2021
作者: Shen, Yuan Wang, Yulin Yang, Shiyong Li, Yan Han, Shiyuan Liu, Zhen Xu, Tao School of Information Science and Engineering University of Jinan Jinan250022 China Highresolution Earth Observation System Shandong Center of Data and Application University of Jinan Jinan250022 China Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan250022 China Shandong Institutes of Industrial Technonlogy Jinan250102 China Land Spatial Data and Remote Sensing Technology Institute of Shandong Province Jinan250002 China
Semantic segmentation of land in remote sensing images plays an important role in urban management and rural planning, and can provide intelligent analysis for urban development. Convolutional neural network (CNN) bas... 详细信息
来源: 评论
Disentangled cascaded Graph Convolution networks for Multi-Behavior Recommendation
arXiv
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arXiv 2024年
作者: Cheng, Zhiyong Dong, Jianhua Liu, Fan Zhu, Lei Yang, Xun Wang, Meng School of Computer Science and Information Engineering Hefei University of Technology No. 485 Danxia Road Anhui Hefei230009 China Shandong Artificial Intelligence Institute Qilu University of Technology Shandong Academy of Sciences No. 19 Keyuan Road Shandong Jinan250014 China School of Computing National University of Singapore 21 Lower Kent Ridge Road Singapore119077 Singapore School of Electronic and Information Engineering University of Tongji No. 4800 Caoan Road Shanghai201804 China School of Information Science and Technology University of Science and Technology of China No. 443 Huangshan Road Anhui Hefei230027 China Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Institute of Artificial Intelligence Hefei Comprehensive National Science Centery No. 485 Danxia Road Anhui Hefei230009 China
Multi-behavioral recommender systems have emerged as a solution to address data sparsity and cold-start issues by incorporating auxiliary behaviors alongside target behaviors. However, existing models struggle to accu... 详细信息
来源: 评论
Zero Stability Well Predicts Performance of Convolutional Neural networks
arXiv
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arXiv 2022年
作者: Chen, Liangming Jin, Long Shang, Mingsheng Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences China Chongqing School University of Chinese Academy of Sciences China School of Information Science and Engineering Lanzhou University China
The question of what kind of convolutional neural network (CNN) structure performs well is fascinating. In this work, we move toward the answer with one more step by connecting zero stability and model performance. Sp... 详细信息
来源: 评论
On the Relation between Quality-Diversity Evaluation and Distribution-Fitting Goal in Text Generation
arXiv
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arXiv 2020年
作者: Li, Jianing Lan, Yanyan Guo, Jiafeng Cheng, Xueqi CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China
The goal of text generation models is to fit the underlying real probability distribution of text. For performance evaluation, quality and diversity metrics are usually applied. However, it is still not clear to what ... 详细信息
来源: 评论
ICT at TREC 2019: Fair Ranking Track  28
ICT at TREC 2019: Fair Ranking Track
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28th Text REtrieval Conference, TREC 2019
作者: Wang, Meng Zhang, Haopeng Liang, Fuhuai Feng, Bin Zhao, Di CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China
In this paper, we will introduce our work in the 2019 TREC fair ranking task. In temporal academic search, more and more people choose to pay attention to the fairness constraints of ranking. The purpose of this task ...
来源: 评论
UniEmoX: Cross-modal Semantic-Guided Large-Scale Pretraining for Universal Scene Emotion Perception
arXiv
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arXiv 2024年
作者: Chen, Chuang Sun, Xiao Liu, Zhi School of Artificial Intelligence Anhui University Hefei230601 China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei230088 China Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machines School of Computer Science and Information Engineering Hefei University of Technology Hefei230009 China Department of Computer and Network Engineering The University of Electro-Communications Chofu-shi Tokyo182-8585 Japan
Visual emotion analysis holds significant research value in both computer vision and psychology. However, existing methods for visual emotion analysis suffer from limited generalizability due to the ambiguity of emoti... 详细信息
来源: 评论
GraphWGAN: Graph Representation Learning with Wasserstein Generative Adversarial networks
GraphWGAN: Graph Representation Learning with Wasserstein Ge...
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International Conference on Big data and Smart computing (BIGCOMP)
作者: Rong Yan Huawei Shen Cao Qi Keting Cen Li Wang College of Big Data Taiyuan University Of Technology Taiyuan China CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China Institute of Computing Technology Beijing China
Graph representation learning aims to represent vertices as low-dimensional and real-valued vectors to facilitate subsequent downstream tasks, i.e., node classification, link predictions. Recently, some novel graph re... 详细信息
来源: 评论
Channel Drop Out:A Simple Way to Prevent CNN from Overfitting in Motor Imagery Based BCI
Channel Drop Out:A Simple Way to Prevent CNN from Overfittin...
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2021国际计算机前沿大会
作者: Jing Luo Yaojie Wang Rong Xu Guangming Liu Xiaofan Wang Yijing Gong Shaanxi Key Laboratory for Network Computing and Security Technology School of Computer Science and EngineeringXi'an University of Technology Shaanxi Province Institute of Water Resources and Electric Power Investigation and Design
With the development of deep learning,many motor imagery brain-computer interfaces based on convolutional neural networks(CNNs) show outstanding ***,the trial number of EEG in the training set is usually limited,and r...
来源: 评论
Graph Reciprocal Neural networks by Abstracting Node as Attribute
Graph Reciprocal Neural Networks by Abstracting Node as Attr...
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IEEE International Conference on data Mining (ICDM)
作者: Liang Yang Jiayi Wang Dongxiao He Chuan Wang Xiaochun Cao Bingxin Niu Zhen Wang School of Artificial Intelligence Hebei University of Technology Tianjin China College of Intelligence and Computing Tianjin University Tianjin China State Key Laboratory of Information Security Institute of Information Engineering CAS Beijing China School of Cyber Science and Technology Shenzhen Campus Sun Yat-sen University Shenzhen China School of Artificial Intelligence OPtics and ElectroNics (iOPEN) School of Cybersecurity Northwestern Polytechnical University Xi’an China
Graph neural network (GNN) can be formulated as the multiplication of the topology-related matrix (adjacency or Laplacian matrix) and node attribute matrix, i.e., operation in node-wise. Unfortunately, this unified fo...
来源: 评论