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| Selection of Observation Position and Orientation in Visual Servoing with Eye-in-vehicle Configuration for Manipulator 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 6, 页码: 761-774
作者: Ma HX(马洪轩) ; Zou W(邹伟); Zhu Z(朱政); Zhang C(张弛); Kang ZB(亢兆兵)
 Adobe PDF(3894Kb) |  收藏 | 浏览/下载：179/46 | 提交时间：2021/06/04
Eye-in-vehicle observation position mobile robot visual servoing pan-tilt camera platform |
| Selection of Observation Position and Orientation in Visual Servoing with Eye-in-vehicle Configuration for Manipulator 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 6, 页码: 761-774
作者: Hong-Xuan Ma; Wei Zou; Zheng Zhu; Chi Zhang; Zhao-Bing Kang
 浏览 | Adobe PDF(3894Kb) | 收藏 | 浏览/下载：180/40 | 提交时间：2021/02/22
Eye-in-vehicle observation position mobile robot visual servoing pan-tilt camera platform. |
| An Advanced Analysis System for Identifying Alcoholic Brain State Through EEG Signals 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 6, 页码: 737-747
作者: Siuly Siuly; Varun Bajaj; Abdulkadir Sengur; Yanchun Zhang
浏览 | Adobe PDF(4171Kb) | 收藏 | 浏览/下载：171/56 | 提交时间：2021/02/22
Electroencephalogram (EEG) alcoholism optimum allocation technique feature extraction decision table. |
| Transfer Hierarchical Attention Network for Generative Dialog System 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 6, 页码: 720-736
作者: Xiang Zhang; Qiang Yang
浏览 | Adobe PDF(1145Kb) | 收藏 | 浏览/下载：108/32 | 提交时间：2021/02/22
Dialog system transfer learning deep learning natural language processing (NLP) artificial intelligence. |
| Development of STEP AP224 Extractor for Interfacing Feature Based CAPP to STEP-NC (AP238) 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 5, 页码: 655-670
作者: Deepanshu Srivastava; Venkateswara Rao Komma
浏览 | Adobe PDF(3913Kb) | 收藏 | 浏览/下载：136/42 | 提交时间：2021/02/22
Reduced-order observer discrete-time systems Lipschitz systems H∞ ARDUINO MEGA 2560 device. |
| Control of a Two-wheeled Machine with Two-directions Handling Mechanism Using PID and PD-FLC Algorithms 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 4, 页码: 511-533
作者: Khaled M. Goher; Sulaiman O. Fadlallah
浏览 | Adobe PDF(2563Kb) | 收藏 | 浏览/下载：151/48 | 提交时间：2021/02/22
Two-wheeled inverted pendulum (IP) with two direction handling Lagrangian formulation proportional-integral-derivative (PID) fuzzy logic control (FLC) under-actuated systems. |
| Pedestrian Height Estimation and 3D Reconstruction Using Pixel-resolution Mapping Method Without Special Patterns 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 4, 页码: 449-461
作者: Bing-Xing Wu; Suat Utku Ay; Ahmed Abdel-Rahim
浏览 | Adobe PDF(6241Kb) | 收藏 | 浏览/下载：143/40 | 提交时间：2021/02/22
Traffic monitoring application spatial resolution pixel-resolution mapping (P-RM) method 3D information pedestrian height estimation. |
| A Hybrid Time Frequency Response and Fuzzy Decision Tree for Non-stationary Signal Analysis and Pattern Recognition 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 3, 页码: 398-412
作者: N. R. Nayak; P. K. Dash; R. Bisoi
浏览 | Adobe PDF(1576Kb) | 收藏 | 浏览/下载：154/50 | 提交时间：2021/02/22
Non-stationary signals sparse S-transform (SST) scaling method fuzzy decision tree pattern classification. |
| Fuzzy Behavior-based Control of Three Wheeled Omnidirectional Mobile Robot 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 2, 页码: 163-185
作者: Nacer Hacene; Boubekeur Mendil
浏览 | Adobe PDF(3450Kb) | 收藏 | 浏览/下载：148/57 | 提交时间：2021/02/22
Three wheeled omnidirectional mobile robot (TWOMR) autonomous navigation obstacle avoidance fuzzy behavior-based control dynamic target dynamic environment. |
| Potential Bands of Sentinel-2A Satellite for Classification Problems in Precision Agriculture 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 1, 页码: 16-26
作者: Tian-Xiang Zhang; Jin-Ya Su; Cun-Jia Liu; Wen-Hua Chen
浏览 | Adobe PDF(1123Kb) | 收藏 | 浏览/下载：196/57 | 提交时间：2021/02/22
Sentinel-2A remote sensing image classification supervised learning precision agriculture. |
