唐朝生  
  唐朝生，男，汉族，中共党员，博士，硕士生导师

主要研究方向:    Graph Neural Networks ，Large Scale Machine Learning
科研情况:        
2018年-2020年，基于特征选择与模板匹配的磁共振快速成像技术研究，河南省科技攻关计划
2013年-2016年，云环境用户多兴趣图谱的移动商务关联性推模型及算法研究，国家自然科学基金一般项目
2012年-2015年，云环境下基于用户兴趣图谱的网络社区营销推荐机理研究，教育部人文社会科学研究规划基金项目

论文情况:     
[1] Twelve-layer deep convolutional neural network with stochastic pooling for tea category classification on GPU platform
[2] Multiple sclerosis identification by convolutional neural network with dropout and parametric ReLU
[3] Multiple Sclerosis Identification by 14-Layer Convolutional Neural Network With Batch Normalization, Dropout, and Stochastic Pooling
[4] High Performance Multiple Sclerosis Classi?cation by Data Augmentation and AlexNet Transfer Learning Model
[5] Hearing loss identification via wavelet entropy and combination of Tabu search and particle swarm optimization
[6] Federated Learning-Based Computation Offloading Optimization in Edge Computing-Supported Internet of Things
[7] Face Recognition Based on Local Gradient Number Pattern and Fuzzy Convex-Concave Partition
[8] Cerebral Micro-Bleeding Detection Based on Densely Connected Neural Network
[9] A label propagation approach based on local optimization
[10] Optimization of selective ensemble for cost-sensitive classification: An empirical study
[11] Alcoholism Identification Based on an AlexNet Transfer Learning Model
[12] Cooperative and Competitive Dynamics Model for Information Propagation in Online Social Networks

电子信箱:        tcs@hpu.edu.cn
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