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[해외논문] Based on machine learning scheme to develop a smart robot embedded with GMM-UBM

Journal of intelligent & fuzzy systems, v.40 no.4, 2021년, pp.7925 - 7937  

Chen, Joy Iong-Zong (Department of Electrical Engineering, Da-Yeh University, Dacun, Changhua, Taiwan (R.O.C.)) ,  Hengjinda, P. (Department of Electrical Engineering, Da-Yeh University, Dacun, Changhua, Taiwan (R.O.C.)) ,  Hsieh, Wen-Hsiang

Abstract AI-Helper 아이콘AI-Helper

Smart Robot embedded with GMM-UBM (Gaussian mixture model- universal background model) based on the machine learning scheme is presented in the article. Authors have designed a smart robot for the farmer and which is designed controlled by the concept of machine learning. On the other hand, the tech...

참고문헌 (20)

  1. Frontiers in Plant Science 7 1 Using deep learning for image-based plant disease detection Mohanty 2016 10.3389/fpls.2016.01419 

  2. IEEE Trans. 50 2071 Wu 2014 

  3. IEEE Intell. Syst. 23 14 Sharkey 2008 10.1109/MIS.2008.60 

  4. IEEE Transactions on Systems, Man, and Cybernetics 36 172 Perceptual learning and abstraction in machine learning: an application to autonomous robotics Bredeche 2006 10.1109/TSMCC.2006.871139 

  5. 10.1109/ICMA.2017.8016120 Hatano M. , Estimation of center of gravity for withdrawal works of unknown indefinite shape rubbles for rescue robots, Proceeding of IEEE International Conference on Mechatronics and Automation (2017), 1970-1975. 

  6. IEEE Transactions on Industrial Informatics 14 3244 GMM and CNN hybrid method for short utterance speaker recognition Liu 2018 10.1109/TII.2018.2799928 

  7. 10.1109/ICEIEC.2019.8784501 Wu Ziteng and Zheng Lin , Emotional Communication Robot Based on 3D FaceModel and ASR Technology, IEEE 9th International Conference on Electronics Information and Emergency Communication (ICEIEC), 2019, 726-730. 

  8. IEEE Transactions on System, Man, and Cybernetics 34 138 Human-robot interaction in rescue robotics Murphy 2004 10.1109/TSMCC.2004.826267 

  9. Ventura R. and Lima P.U. , Search and rescue robot: the civil protection teams of the future, Third International Conference on Emerging Security Technologies (2012), 12-19. 

  10. 10.1109/URAI.2017.7992670 Shin S. , Yoon D. , Song H. , Kim B. and Han J. , Communication System of a Segmented Rescue Robot Utilizing Socket Programming and ROS, The 14th International Conference onUbiquitousRobots andAmbient Intelligence, 2017, 565-569. 

  11. 10.1109/URAI.2016.7734045 Park J. , Yun D. , Park D. and Park C. , Dynamic Simulation of Joint Module with MR Damper for Mobile Rescue Robot, The 13th International Conference on Ubiquitous Robots and Ambient Intelligence, 2016, 157-158 

  12. IEEE Access 7 14124 Efficient laser-based 3D SLAM for coal mine rescue robots Li 2019 10.1109/ACCESS.2018.2889304 

  13. 10.1109/ICISET.2016.7856489 Uddin Z. and Islam M. , Search and Rescue System for Alive Human Detection by Semi-autonomous Mobile Rescue Robot, the International Conference on Innovations in Science, Engineering and Technology, 2016. 

  14. 10.1109/ICCIDS.2019.8862041 Kanimozhi S. , Gayathri G. and Mala T. , Multiple Real-time object identification using Single shot Multi-Box detection, the 2nd International Conference on Computational Intelligence in Data Science, 2019. 

  15. 10.1109/ICIP.2018.8451034 Kim J.U. , Kwon J. , Kim H.G. , Lee H. and Ro Y.M. , Object Bounding Box-Critic Networks for Occlusion-Robust Object Detection in Road Scene, the 25th IEEE International Conference on Image Processing, 2018, 1313-1317. 

  16. 10.1109/ICCE-TW.2014.6904109 Ju T.F. , Lu W.M. , Chen K.H. and Guo J.I. , Vision-based moving objects detection for intelligent automobiles and a robustness enhancing method, IEEE International Conference on Consumer Electronics - Taiwan, 2014, 75-76. 

  17. 10.1109/ICCONS.2018.8662921 Mane S. and Mangle S. , Moving object detection and tracking Using Convolutional Neural Networks, the 2nd International Conference on Intelligent Computing and Control Systems, 2018, 1809-1813. 

  18. 10.1109/ICIVC.2018.8492803 Yu L. , Chen X. and Zhou S. , Research of image main objects detection algorithm based on deep learning, the 3rd IEEE International Conference on Image, Vision and Computing, 2018, 70-75. 

  19. 10.1109/ICICES.2014.7033891 Bharath R.R. and Dhivya G. , Moving Object Detection, Classification and its Parametric Evaluation, International Conference on Information Communication and Embedded Systems, 2014. 

  20. 10.1109/CVPR.2016.308 Szegedy C. , Vanhoucke V. , Ioffe S. , Shlens J. and Wojna Z. , Re-thinking the Inception Architecture for Computer-Vision, IEEE Conference on ComputerVision and Pattern Recognition (CVPR), 2016, 2818-2826. 

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