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EEG-Based Spatio-Temporal Convolutional Neural Network for Driver Fatigue Evaluation
EEG-Based Spatio-Temporal Convolutional Neural Network for Driver Fatigue Evaluation
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EEG-Based Spatio-Temporal Convolutional Neural Network for Driver Fatigue Evaluation

Gao, Zhongke ; Wang, Xinmin ; Yang, Yuxuan ; Mu, Chaoxu ; Cai, Qing ; Dang, Weidong ; Zuo, Siyang

IEEE transaction on neural networks and learning systems, 2019-09, Vol.30 (9), p.2755-2763

United States: IEEE

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12
A Mutually Supervised Graph Attention Network for Few-Shot Segmentation: The Perspective of Fully Utilizing Limited Samples
A Mutually Supervised Graph Attention Network for Few-Shot Segmentation: The Perspective of Fully Utilizing Limited Samples
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A Mutually Supervised Graph Attention Network for Few-Shot Segmentation: The Perspective of Fully Utilizing Limited Samples

Gao, Honghao ; Xiao, Junsheng ; Yin, Yuyu ; Liu, Tong ; Shi, Jiangang

IEEE transaction on neural networks and learning systems, 2024-04, Vol.35 (4), p.1-13

United States: IEEE

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13
Applications of Deep Learning and Reinforcement Learning to Biological Data
Applications of Deep Learning and Reinforcement Learning to Biological Data
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Applications of Deep Learning and Reinforcement Learning to Biological Data

Mahmud, Mufti ; Kaiser, Mohammed Shamim ; Hussain, Amir ; Vassanelli, Stefano

IEEE transaction on neural networks and learning systems, 2018-06, Vol.29 (6), p.2063-2079

United States: IEEE

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14
Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review
Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review
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Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review

Li, Ying ; Ma, Lingfei ; Zhong, Zilong ; Liu, Fei ; Chapman, Michael A. ; Cao, Dongpu ; Li, Jonathan

IEEE transaction on neural networks and learning systems, 2021-08, Vol.32 (8), p.3412-3432

IEEE

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15
Cost-Sensitive Learning of Deep Feature Representations From Imbalanced Data
Cost-Sensitive Learning of Deep Feature Representations From Imbalanced Data
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Cost-Sensitive Learning of Deep Feature Representations From Imbalanced Data

Khan, Salman H. ; Hayat, Munawar ; Bennamoun, Mohammed ; Sohel, Ferdous A. ; Togneri, Roberto

IEEE transaction on neural networks and learning systems, 2018-08, Vol.29 (8), p.3573-3587

United States: IEEE

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16
Extreme Learning Machine for Multilayer Perceptron
Extreme Learning Machine for Multilayer Perceptron
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Extreme Learning Machine for Multilayer Perceptron

Tang, Jiexiong ; Deng, Chenwei ; Huang, Guang-Bin

IEEE transaction on neural networks and learning systems, 2016-04, Vol.27 (4), p.809-821

United States: IEEE

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17
Regularizing Hyperspectral and Multispectral Image Fusion by CNN Denoiser
Regularizing Hyperspectral and Multispectral Image Fusion by CNN Denoiser
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Regularizing Hyperspectral and Multispectral Image Fusion by CNN Denoiser

Dian, Renwei ; Li, Shutao ; Kang, Xudong

IEEE transaction on neural networks and learning systems, 2021-03, Vol.32 (3), p.1124-1135

United States: IEEE

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18
Output Reachable Set Estimation and Verification for Multilayer Neural Networks
Output Reachable Set Estimation and Verification for Multilayer Neural Networks
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Output Reachable Set Estimation and Verification for Multilayer Neural Networks

Xiang, Weiming ; Tran, Hoang-Dung ; Johnson, Taylor T.

IEEE transaction on neural networks and learning systems, 2018-11, Vol.29 (11), p.5777-5783

United States: IEEE

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19
Adaptive Fuzzy Neural Network Control for a Constrained Robot Using Impedance Learning
Adaptive Fuzzy Neural Network Control for a Constrained Robot Using Impedance Learning
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Adaptive Fuzzy Neural Network Control for a Constrained Robot Using Impedance Learning

He, Wei ; Dong, Yiting

IEEE transaction on neural networks and learning systems, 2018-04, Vol.29 (4), p.1174-1186

United States: IEEE

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Learning a Low Tensor-Train Rank Representation for Hyperspectral Image Super-Resolution
Learning a Low Tensor-Train Rank Representation for Hyperspectral Image Super-Resolution
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Learning a Low Tensor-Train Rank Representation for Hyperspectral Image Super-Resolution

Dian, Renwei ; Li, Shutao ; Fang, Leyuan

IEEE transaction on neural networks and learning systems, 2019-09, Vol.30 (9), p.2672-2683

United States: IEEE

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