中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共74条，第1-10条 帮助

限定条件    
已选(0)清除 条数/页：   排序方式：
An Immersive Virtual Reality System for Rodents in Behavioral and Neural Research 期刊论文
International Journal of Automation and Computing, 2021, 期号: 18(5), 页码: 838-848
作者:  Li Liu;  Zi-yang Wang;  Yu Liu;  Chun Xu
Adobe PDF(1271Kb)  |  收藏  |  浏览/下载：251/66  |  提交时间：2022/04/07
Virtual space  flexible control  multi-sensory interactions  visual programming  context cognition  
Data Augmentation and Deep Neuro-fuzzy Network for Student Performance Prediction with MapReduce Framework 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 981-992
作者:  Amlan Jyoti Baruah;  Siddhartha Baruah
Adobe PDF(1583Kb)  |  收藏  |  浏览/下载：189/49  |  提交时间：2021/11/26
Educational data mining (EDA)  MapReduce framework  deep neuro-fuzzy network  student performance  data augmentation  
Encoding-decoding Network With Pyramid Self-attention Module for Retinal Vessel Segmentation 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 973-980
作者:  Cong-Zhong Wu;  Jun Sun;  Jing Wang;  Liang-Feng Xu;  Shu Zhan
Adobe PDF(1416Kb)  |  收藏  |  浏览/下载：163/37  |  提交时间：2021/11/26
Retina vessel segmentation  deep learning  U-Net  attention mechanism  medical image  
DLA+: A Light Aggregation Network for Object Classification and Detection 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 963-972
作者:  Fu-Tian Wang;  Li Yang;  Jin Tang;  Si-Bao Chen;  Xin Wang
Adobe PDF(1212Kb)  |  收藏  |  浏览/下载：172/27  |  提交时间：2021/11/26
Light weight  image classification  channel attention  efficient convolution  object detection  
Supervised and Semi-supervised Methods for Abdominalm Organ Segmentation: A Review 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 887-914
作者:  Isaac Baffour Senkyire;  Zhe Liu
Adobe PDF(1308Kb)  |  收藏  |  浏览/下载：208/47  |  提交时间：2021/11/26
Abdominal organ, supervised segmentation  semi-supervised segmentation  evaluation metrics  image segmentation  machine learning  
Fault Classification for On-board Equipment of High-speed Railway Based on Attention Capsule Network 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 5, 页码: 814-825
作者:  Lu-Jie Zhou;  Jian-Wu Dang;  Zhen-Hai Zhan
Adobe PDF(1208Kb)  |  收藏  |  浏览/下载：213/50  |  提交时间：2021/09/13
On-board equipment  fault classification  capsule network  attention mechanism  focal loss  
STRNet: Triple-stream Spatiotemporal Relation Network for Action Recognition 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 5, 页码: 718-730
作者:  Zhi-Wei Xu;  Xiao-Jun Wu;  Josef Kittler
Adobe PDF(1129Kb)  |  收藏  |  浏览/下载：169/40  |  提交时间：2021/09/13
Action recognition  spatiotemporal relation  multi-branch fusion  long-term representation  video classification  
Designing an Intelligent Control Philosophy in Reservoirs of Water Transfer Networks in Supervisory Control and Data Acquisition System Stations 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 5, 页码: 694-717
作者:  Ali Dolatshahi Zand, Kaveh Khalili-Damghani, Sadigh Raissi
Adobe PDF(9772Kb)  |  收藏  |  浏览/下载：173/42  |  提交时间：2021/09/13
Water demand forecasting  water transfer network  supervisory control and data acquisition  water management, multi-core artificial neural network, fuzzy inference system  
Ensuring the Correctness of Regular Expressions: A Review 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 4, 页码: 521-535
作者:  Li-Xiao Zheng;  Shuai Ma;  Zu-Xi Chen;  Xiang-Yu Luo
Adobe PDF(1076Kb)  |  收藏  |  浏览/下载：112/30  |  提交时间：2021/07/20
Regular expressions  correctness  string generation  learning  static checking  verification  visualization, repairing  
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：285/58  |  提交时间：2021/05/24
Reputation system  rating aggregation  machine learning  consumer reliability  user trust