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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：223/53  |  提交时间：2021/11/26
Educational data mining (EDA)  MapReduce framework  deep neuro-fuzzy network  student performance  data augmentation  
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：245/33  |  提交时间：2021/11/26
Light weight  image classification  channel attention  efficient convolution  object detection  
Fault Information Recognition for On-board Equipment of High-speed Railway Based on Multi-neural Network Collaboration 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 935-946
作者:  Lu-Jie Zhou;  Jian-Wu Dang;  Zhen-Hai Zhang
Adobe PDF(1263Kb)  |  收藏  |  浏览/下载：249/55  |  提交时间：2021/11/26
Train control system  Chinese named entity recognition (NER)  character feature  gating mechanism  bidirectional long short-term memory (BiLSTM)  
Improved Network for Face Recognition Based on Feature Super Resolution Method 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 915-925
作者:  Ling-Yi Xu;  Zoran Gajic
Adobe PDF(1989Kb)  |  收藏  |  浏览/下载：210/51  |  提交时间：2021/11/26
Face recognition  feature super resolution  multiple-branch network  deep learning  convolutional neural networks  
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：252/53  |  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：255/59  |  提交时间：2021/09/13
On-board equipment  fault classification  capsule network  attention mechanism  focal loss  
Robust Optimal Higher-order-observer-based Dynamic Sliding Mode Control for VTOL Unmanned Aerial Vehicles 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 5, 页码: 802-813
作者:  Yashar Mousavi;  Amin Zarei;  Arash Mousavi;  Mohsen Biari
Adobe PDF(4822Kb)  |  收藏  |  浏览/下载：222/44  |  提交时间：2021/09/13
Unmanned aerial vehicle  dynamic sliding mode  trajectory tracking  fractional firefly algorithm  vertical take-off and landing system  
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：203/52  |  提交时间：2021/09/13
Action recognition  spatiotemporal relation  multi-branch fusion  long-term representation  video classification  
Dynamic System Identification of Underwater Vehicles Using Multi-output Gaussian Processes 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 5, 页码: 681-693
作者:  Wilmer Ariza Ramirez;  Juš Kocijan;  Zhi Quan Leong;  Hung Duc Nguyen;  Shantha Gamini Jayasinghe
Adobe PDF(3231Kb)  |  收藏  |  浏览/下载：229/54  |  提交时间：2021/09/13
Dependent Gaussian processes  dynamic system identification  multi-output Gaussian processes  non-parametric identification  autonomous underwater vehicle (AUV)  
A Novel Heterogeneous Actor-critic Algorithm with Recent Emphasizing Replay Memory 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 4, 页码: 619-631
作者:  Bao Xi;  Rui Wang;  Ying-Hao Cai;  TaoLu;  Shuo Wang
Adobe PDF(2505Kb)  |  收藏  |  浏览/下载：201/59  |  提交时间：2021/07/20
Reinforcement learning (RL)  actor-critic  experience replay  training efficiency  manipulation skill learning