CASIA OpenIR

浏览/检索结果: 共6条,第1-6条 帮助

限定条件    
已选(0)清除 条数/页:   排序方式:
Evolutionary Computation for Large-scale Multi-objective Optimization: A Decade of Progresses 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 2, 页码: 155-169
作者:  Wen-Jing Hong;  Peng Yang;  Ke Tang
Adobe PDF(946Kb)  |  收藏  |  浏览/下载:128/34  |  提交时间:2021/04/22
Large-scale multi-objective optimization  high-dimensional search space  evolutionary computation  evolutionary algorithms  scalability  
Application of Machine Learning for Online Reputation 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 3, 页码: 492-502
作者:  Ahmad Alqwadri;  Mohammad Azzeh;  Fadi Almasalha
Adobe PDF(1091Kb)  |  收藏  |  浏览/下载:277/56  |  提交时间:2021/05/24
Reputation system  rating aggregation  machine learning  consumer reliability  user trust  
Knowing Your Dog Breed: Identifying a Dog Breed with Deep Learning 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 1, 页码: 45-54
作者:  Punyanuch Borwarnginn;  Worapan Kusakunniran;  Sarattha Karnjanapreechakorn;  Kittikhun Thongkanchorn
Adobe PDF(1149Kb)  |  收藏  |  浏览/下载:181/67  |  提交时间:2021/02/23
Computer vision  deep learning  dog breed classification  transfer learning  image augmentation  
An Approach to Reducing Input Parameter Volume for Fault Classifiers 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 2, 页码: 199-212
作者:  Ann Smith;  Fengshou Gu;  Andrew D. Ball
Adobe PDF(1085Kb)  |  收藏  |  浏览/下载:115/53  |  提交时间:2021/02/22
Fault diagnosis  classification  variable clustering  data compression  big data.  
A Survey on Deep Learning-based Fine-grained Object Classification and Semantic Segmentation 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 2, 页码: 119-135
作者:  Bo Zhao;  Jiashi Feng;  Xiao Wu;  Shuicheng Yan
Adobe PDF(5409Kb)  |  收藏  |  浏览/下载:164/36  |  提交时间:2021/02/23
Deep learning  fine-grained image classi¯cation  semantic segmentation  convolutional neural network (CNN)  recurrent neural network (RNN).  
An Effective Density Based Approach to Detect Complex Data Clusters Using Notion of Neighborhood Difference 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 1, 页码: 57-67
作者:  S. Nagaraju;  Manish Kashyap;  Mahua Bhattachraya
浏览  |  Adobe PDF(30557Kb)  |  收藏  |  浏览/下载:105/29  |  提交时间:2021/02/23
Density based clustering  neighborhood difference  density-based spatial clustering of applications with noise (DBSCAN)  space density indexing (SDI)  core object.