兰州大学机构库

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Convolutional Neural Network Based on Complex Networks for Brain Tumor Image Classification with a Modified Activation Function 期刊论文
IEEE Access, 2020, 卷号: 8, 页码: 89281-89290
Authors:  Huang, Zhiguan;  Du, Xiaohao;  Chen, Liangming;  Li, Yuhe;  Liu, M(刘梅);  Chou, Yao;  Jin, L(金龙)
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Convolutional Neural Network Based on Complex Networks for Brain Tumor Image Classification With a Modified Activation Function 期刊论文
IEEE Access, 2020, 卷号: 8, 页码: 89281-89290
Authors:  Z. Huang;  X. Du;  L. Chen;  Y. Li;  M. Liu;  Y. Chou;  L. Jin
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Convolutional neural network  complex networks  randomly generated graph  network generator  brain tumors  
Effects of Dietary Energy Levels on Rumen Fermentation, Microbial Diversity, and Feed Efficiency of Yaks (Bos grunniens) 期刊论文
Frontiers in Microbiology, 2020, 卷号: 11
Authors:  Ahmad, Anum Ali;  Yang, Chao;  Zhang, Jianbo;  Kalwar, Qudratullah;  Liang, Zeyi;  Li, Chen;  Du, Mei;  Yan, Ping;  Long, Ruijun;  Han, Jianlin...Ahmad, Anum Ali;  Yang, Chao;  Zhang, Jianbo;  Kalwar, Qudratullah;  Liang, Zeyi;  Li, Chen;  Du, Mei;  Yan, Ping;  Long, Ruijun;  Han, Jianlin;  Ding, Xuezhi
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yak  dietary energy  rumen microbiota  volatile fatty acid  feed efficiency  growth performance  
A Deep Learning Approach for Mild Depression Recognition Based on Functional Connectivity Using Electroencephalography 期刊论文
FRONTIERS IN NEUROSCIENCE, 2020, 卷号: 14
Authors:  Li, Xiaowei;  La, Rong;  Wang, Ying;  Hu, Bin;  Zhang, Xuemin
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EEG  functional connectivity  convolutional neural network  mild depression  classification  
Pain-Evoked Reorganization in Functional Brain Networks 期刊论文
CEREBRAL CORTEX, 2020, 卷号: 30, 期号: 5, 页码: 2804-2822
Authors:  Zheng, Weihao;  Woo, Choong-Wan;  Yao, Zhijun;  Goldstein, Pavel;  Atlas, Lauren Y.;  Roy, Mathieu;  Schmidt, Liane;  Krishnan, Anjali;  Jepma, Marieke;  Hu, Bin...Zheng, Weihao;  Woo, Choong-Wan;  Yao, Zhijun;  Goldstein, Pavel;  Atlas, Lauren Y.;  Roy, Mathieu;  Schmidt, Liane;  Krishnan, Anjali;  Jepma, Marieke;  Hu, Bin;  Wager, Tor D.
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functional network  hub disruption  inter-system connectivity  immediate pain  reorganization  
Esophagus Segmentation in Computed Tomography Images Using a U-Net Neural Network With a Semiautomatic Labeling Method 期刊论文
IEEE Access, 2020, 卷号: 8, 期号: *, 页码: 202459-202468
Authors:  Lou, Xiao;  Zhu, Youzhe;  Punithakumar, Kumaradevan;  Le, Lawrence H.;  Li, Baosheng
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Computed Tomography  Deep Learning  Esophagus  Segmentation  U-net  Automation  Computerized tomography  Deep learning  Image segmentation  Learning systems  Three dimensional computer graphicsComputed tomography images  Convex-hull approach  Experimental evaluation  Level set algorithm  Segmentation methods  Segmentation results  Semiautomatic methods  Topological levels  
A New Automatic Parameter Setting Method of a Simplified PCNN for Image Segmentation 期刊论文
IEEE T NEURAL NETWOR, 2011, 卷号: 22, 期号: 6, 页码: 880-892
Authors:  Yuli Chen;  Sung-Kee Park;  Ma, YD(马义德);  Rajeshkanna Ala
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Automatic parameter setting  dynamic property  general formulae  image segmentation  optimal histogram threshold  simplified pulse coupled neural network  standard deviation  static property  sub-intensity range  
Prediction of programmed-temperature retention values of naphthas by artificial neural networks 期刊论文
SAR AND QSAR IN ENVIRONMENTAL RESEARCH, 2000, 卷号: 11, 期号: 2
Authors:  Qi, JH;  Zhang, XY(张晓昀);  Zhang, RS(张瑞生);  Liu, MC;  Hu, ZD(胡之德);  Xue, HF;  Fan, BT;  Fan, BT (reprint author), Univ Paris 07, ITODYS, 1 Rue Guy de La Brosse, F-75005 Paris, France.
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capillary gas chromatography  artificial neural networks  retention index  density  cross-validation  
Transient dynamics of sparsely connected Hopfield neural networks with arbitrary degree distributions 期刊论文
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2008, 卷号: 387, 期号: 4, 页码: 1009-1015
Authors:  Zhang, P;  Chen, Y;  Chen, Y (reprint author), Lanzhou Univ, Inst Theoret Phys, Lanzhou 730000, Peoples R China.
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neural networks  complex networks  degree distribution  probability theory  
Optimal parameters selection for BP neural network based on particle swarm optimization: A case study of wind speed forecasting 期刊论文
KNOWLEDGE-BASED SYSTEMS, 2014, 卷号: 56, 页码: 226-239
Authors:  Ren, C;  An, N;  Wang, JZ;  Li, L;  Hu, B;  Shang, D;  An, N (reprint author), Lanzhou Univ, Sch Informat Sci & Engn, Adv Comp Lab, Lanzhou 730000, Gansu, Peoples R China.
Adobe PDF(3946Kb)  |  Favorite  |    Submit date:2015/12/16
BP neural network  Input parameters selection  Particle swarm optimization algorithm  Wind speed  Wind forecasting