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396 results on '"Dong, Fangyan"'

1. Design and Analysis of a Lower Limb Rehabilitation Robot with Movement in Three-Dimensional Space

Author

Yu, Long, Feng, Yongfei, Dong, Fangyan, Wang, Hongbo, Li, Haoyu, Shen, Tao, Liang, Dan, Vladareanu, Victor, Celebi, Emre, Series Editor, Chen, Jingdong, Series Editor, Gopi, E. S., Series Editor, Neustein, Amy, Series Editor, Liotta, Antonio, Series Editor, Di Mauro, Mario, Series Editor, Shaikh, Asadullah, editor, Alghamdi, Abdullah, editor, Tan, Qing, editor, and El Emary, Ibrahiem M. M., editor

Published
2024
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4. Research on Slide-Stainer Layout Dynamic Optimization

Author

Yang, Debin, Liu, Bingxian, Wang, Kehui, Gui, Kun, Chen, Kewei, Dong, Fangyan, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, S. Shmaliy, Yuriy, editor, and Nayyar, Anand, editor

Published
2023
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5. Chinese Character Writing Evaluation System Based on Image Processing

Author

Li, Renwei, Zhang, Zheyan, Shi, Weiwei, Dong, Fangyan, Chen, Kewei, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, S. Shmaliy, Yuriy, editor, and Nayyar, Anand, editor

Published
2023
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6. Research on Recognition Method of Cashmere and Wool Mixed Fiber Based on DFS-YOLOv5

Author

Zeng, Can, Liu, Youna, Zhu, Jinhua, Dong, Fangyan, Chen, Kewei, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, S. Shmaliy, Yuriy, editor, and Nayyar, Anand, editor

Published
2023
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7. Age Estimation and Gender Recognition Based on Canny-MobileNetV2

Author

Hu, Pengfei, Wang, Yu, Dong, Fangyan, Chen, Kewei, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, S. Shmaliy, Yuriy, editor, and Nayyar, Anand, editor

Published
2023
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16. FFD-SLAM: A Real-Time Visual SLAM Toward Dynamic Scenes with Semantic and Optical Flow Information.

Author

Zhang, Hao, Wang, Yu, Zhong, Tianjie, Dong, Fangyan, and Chen, Kewei

Subjects
OPTICAL flow, OBJECT recognition (Computer vision), DYNAMICAL systems, PROBLEM solving, POINT set theory
Abstract

To solve the problem of poor localization accuracy and robustness of visual simultaneous localization and mapping (SLAM) systems in highly dynamic environments, this paper proposes a dynamic visual SLAM algorithm called FFD-SLAM that fuses the target detection network with the optical flow method. The algorithm considers ORB-SLAM2 as the basic framework, joins the semantic thread in parallel with its tracking thread, initially obtains the set of feature points through the real-time detection of dynamic objects in the environment through YOLOv5 in the semantic thread, then filters the set of feature points obtained in the semantic thread through the optical flow module, and finally utilizes the remaining static feature points for the matching calculation. Experiments showed that the proposed algorithm showed an improvement of approximately 97% in the localization accuracy compared with the ORB-SLAM2 algorithm in a highly dynamic environment, which effectively improves the localization accuracy and robustness of the system. The proposed algorithm also showed a higher real-time performance compared with some excellent dynamic SLAM algorithms. [ABSTRACT FROM AUTHOR]

Published
2024
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18. Intent expression using eye robot for mascot robot system

Author

Yamazaki, Yoichi, Dong, Fangyan, Masuda, Yuta, Uehara, Yukiko, Kormushev, Petar, Vu, Hai An, Le, Phuc Quang, and Hirota, Kaoru

Subjects
Computer Science - Robotics, Computer Science - Artificial Intelligence, Computer Science - Human-Computer Interaction
Abstract

An intent expression system using eye robots is proposed for a mascot robot system from a viewpoint of humatronics. The eye robot aims at providing a basic interface method for an information terminal robot system. To achieve better understanding of the displayed information, the importance and the degree of certainty of the information should be communicated along with the main content. The proposed intent expression system aims at conveying this additional information using the eye robot system. Eye motions are represented as the states in a pleasure-arousal space model. Changes in the model state are calculated by fuzzy inference according to the importance and degree of certainty of the displayed information. These changes influence the arousal-sleep coordinates in the space that corresponds to levels of liveliness during communication. The eye robot provides a basic interface for the mascot robot system that is easy to be understood as an information terminal for home environments in a humatronics society., Comment: 5 pages

Published
2009

19. Fuzzy inference based mentality estimation for eye robot agent

Author

Yamazaki, Yoichi, Dong, Fangyan, Masuda, Yuta, Uehara, Yukiko, Kormushev, Petar, Vu, Hai An, Le, Phuc Quang, and Hirota, Kaoru

Subjects
Computer Science - Robotics, Computer Science - Artificial Intelligence, Computer Science - Human-Computer Interaction
Abstract

Household robots need to communicate with human beings in a friendly fashion. To achieve better understanding of displayed information, an importance and a certainty of the information should be communicated together with the main information. The proposed intent expression system aims to convey this additional information using an eye robot. The eye motions are represented as states in a pleasure-arousal space model. Change of the model state is calculated by fuzzy inference according to the importance and certainty of the displayed information. This change influences the arousal-sleep coordinate in the space which corresponds to activeness in communication. The eye robot provides a basic interface for the mascot robot system which is an easy to understand information terminal for home environments in a humatronics society., Comment: 2 pages, in Japanese

Published
2009

20. Eligibility Propagation to Speed up Time Hopping for Reinforcement Learning

Author

Kormushev, Petar, Nomoto, Kohei, Dong, Fangyan, and Hirota, Kaoru

Subjects
Computer Science - Artificial Intelligence, Computer Science - Learning, Computer Science - Robotics
Abstract

A mechanism called Eligibility Propagation is proposed to speed up the Time Hopping technique used for faster Reinforcement Learning in simulations. Eligibility Propagation provides for Time Hopping similar abilities to what eligibility traces provide for conventional Reinforcement Learning. It propagates values from one state to all of its temporal predecessors using a state transitions graph. Experiments on a simulated biped crawling robot confirm that Eligibility Propagation accelerates the learning process more than 3 times., Comment: 7 pages

Published
2009

21. Time Hopping technique for faster reinforcement learning in simulations

Author

Kormushev, Petar, Nomoto, Kohei, Dong, Fangyan, and Hirota, Kaoru

Subjects
Computer Science - Artificial Intelligence, Computer Science - Learning, Computer Science - Robotics
Abstract

This preprint has been withdrawn by the author for revision, Comment: This preprint has been withdrawn by the author for revision

Published
2009

22. Time manipulation technique for speeding up reinforcement learning in simulations

Author

Kormushev, Petar, Nomoto, Kohei, Dong, Fangyan, and Hirota, Kaoru

Subjects
Computer Science - Artificial Intelligence, Computer Science - Learning, Computer Science - Robotics
Abstract

A technique for speeding up reinforcement learning algorithms by using time manipulation is proposed. It is applicable to failure-avoidance control problems running in a computer simulation. Turning the time of the simulation backwards on failure events is shown to speed up the learning by 260% and improve the state space exploration by 12% on the cart-pole balancing task, compared to the conventional Q-learning and Actor-Critic algorithms., Comment: 12 pages

Published
2009

23. Semantic Similarity Analysis via Syntax Dependency Structure and Gate Recurrent Unit.

Author

Kang, Qiao, Kan, Jing, Dong, Fangyan, and Chen, Kewei

Subjects
NATURAL language processing, SYNTAX (Grammar), TASK analysis, NATURAL languages
Abstract

Sentences are composed of words, phrases, and clauses. The relationship between them is usually tree-like. In the hierarchical structure of the sentence, the dependency relationships between different components affect the syntactic structure. Syntactic structure is very important for understanding the meaning of the whole sentence. However, the gated recursive unit (GRU) models cannot fully encode hierarchical syntactic dependencies, which leads to its poor performance in various natural language tasks. In this paper, a model called relative syntactic distance bidirectional gated recursive unit (RSD-BiGRU) is constructed to capture syntactic structure dependencies. The model modifies the gating mechanism in GRU through relative syntactic distance. It also offers a transformation gate to model the syntactic structure more directly. Embedding sentence meanings with sentence structure dependency into dense vectors. This model is used to conduct semantic similarity experiments on the QQP and SICK datasets. The results show that the sentence representation obtained by RSD-BiGRU model contains more semantic information. This is helpful for semantic similarity analysis tasks. [ABSTRACT FROM AUTHOR]

Published
2024
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49. Image Retrieval Based on Similarity Score Fusion from Feature Similarity Ranking Lists

Author

Jović, Mladen, Hatakeyama, Yutaka, Dong, Fangyan, Hirota, Kaoru, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Wang, Lipo, editor, Jiao, Licheng, editor, Shi, Guanming, editor, Li, Xue, editor, and Liu, Jing, editor

Published
2006
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