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1
Offloading in Internet of Vehicles: A Fog-Enabled Real-Time Traffic Management System
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Offloading in Internet of Vehicles: A Fog-Enabled Real-Time Traffic Management System

Wang, Xiaojie ; Ning, Zhaolong ; Wang, Lei

IEEE transactions on industrial informatics, 2018-10, Vol.14 (10), p.4568-4578

Piscataway: IEEE

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2
Relaxed Real-Time Scheduling Stabilization of Discrete-Time Takagi-Sugeno Fuzzy Systems via An Alterable-Weights-Based Ranking Switching Mechanism
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Relaxed Real-Time Scheduling Stabilization of Discrete-Time Takagi-Sugeno Fuzzy Systems via An Alterable-Weights-Based Ranking Switching Mechanism

Xie, Xiangpeng ; Yue, Dong ; Peng, Chen

IEEE transactions on fuzzy systems, 2018-12, Vol.26 (6), p.3808-3819 [Periódico revisado por pares]

New York: IEEE

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3
Optimal Real-Time Operation Strategy for Microgrid: An ADP-Based Stochastic Nonlinear Optimization Approach
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Optimal Real-Time Operation Strategy for Microgrid: An ADP-Based Stochastic Nonlinear Optimization Approach

Shuai, Hang ; Fang, Jiakun ; Ai, Xiaomeng ; Wen, Jinyu ; He, Haibo

IEEE transactions on sustainable energy, 2019-04, Vol.10 (2), p.931-942 [Periódico revisado por pares]

Piscataway: IEEE

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4
Fault Detection and Faulted Line Identification in Active Distribution Networks Using Synchrophasors-Based Real-Time State Estimation
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Fault Detection and Faulted Line Identification in Active Distribution Networks Using Synchrophasors-Based Real-Time State Estimation

Pignati, Marco ; Zanni, Lorenzo ; Romano, Paolo ; Cherkaoui, Rachid ; Paolone, Mario

IEEE transactions on power delivery, 2017-02, Vol.32 (1), p.381-392 [Periódico revisado por pares]

IEEE

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5
Real-Time Detection of Apple Leaf Diseases Using Deep Learning Approach Based on Improved Convolutional Neural Networks
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Artigo
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Real-Time Detection of Apple Leaf Diseases Using Deep Learning Approach Based on Improved Convolutional Neural Networks

Jiang, Peng ; Chen, Yuehan ; Liu, Bin ; He, Dongjian ; Liang, Chunquan

IEEE access, 2019, Vol.7, p.59069-59080 [Periódico revisado por pares]

Piscataway: IEEE

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6
Real-Time Coordinated Voltage Control of PV Inverters and Energy Storage for Weak Networks With High PV Penetration
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Artigo
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Real-Time Coordinated Voltage Control of PV Inverters and Energy Storage for Weak Networks With High PV Penetration

Wang, Licheng ; Bai, Feifei ; Yan, Ruifeng ; Saha, Tapan Kumar

IEEE transactions on power systems, 2018-05, Vol.33 (3), p.3383-3395 [Periódico revisado por pares]

New York: IEEE

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7
Real-Time Faulted Line Localization and PMU Placement in Power Systems Through Convolutional Neural Networks
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Real-Time Faulted Line Localization and PMU Placement in Power Systems Through Convolutional Neural Networks

Li, Wenting ; Deka, Deepjyoti ; Chertkov, Michael ; Wang, Meng

IEEE transactions on power systems, 2019-11, Vol.34 (6), p.4640-4651 [Periódico revisado por pares]

New York: IEEE

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8
Multi-Scale Deep Reinforcement Learning for Real-Time 3D-Landmark Detection in CT Scans
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Multi-Scale Deep Reinforcement Learning for Real-Time 3D-Landmark Detection in CT Scans

Ghesu, Florin-Cristian ; Georgescu, Bogdan ; Zheng, Yefeng ; Grbic, Sasa ; Maier, Andreas ; Hornegger, Joachim ; Comaniciu, Dorin

IEEE transactions on pattern analysis and machine intelligence, 2019-01, Vol.41 (1), p.176-189 [Periódico revisado por pares]

United States: IEEE

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9
Deep Dual-Resolution Networks for Real-Time and Accurate Semantic Segmentation of Traffic Scenes
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Deep Dual-Resolution Networks for Real-Time and Accurate Semantic Segmentation of Traffic Scenes

Pan, Huihui ; Hong, Yuanduo ; Sun, Weichao ; Jia, Yisong

IEEE transactions on intelligent transportation systems, 2023-03, Vol.24 (3), p.3448-3460 [Periódico revisado por pares]

New York: IEEE

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10
Real-Time Video Emotion Recognition Based on Reinforcement Learning and Domain Knowledge
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Real-Time Video Emotion Recognition Based on Reinforcement Learning and Domain Knowledge

Zhang, Ke ; Li, Yuanqing ; Wang, Jingyu ; Cambria, Erik ; Li, Xuelong

IEEE transactions on circuits and systems for video technology, 2022-03, Vol.32 (3), p.1034-1047 [Periódico revisado por pares]

New York: IEEE

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