In the recognition of Chinese handwritten characters,it is a pattern matching process with large number of standard *** is the bottleneck of the recognition *** this paper,a multi-layered pipeline architecture is devi...
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In the recognition of Chinese handwritten characters,it is a pattern matching process with large number of standard *** is the bottleneck of the recognition *** this paper,a multi-layered pipeline architecture is devised to solve this bottleneck. The technology of multi-bank storage,parallel computing,*** also implemented to optimize the ***,a high recognition speed is *** experimental system is implemented on a Xilinx XC4013E FPGA *** will be migrated to a custom VLSI chip in the future.
Simulation under Virtual Reality is the front edge of simulation technology. And also, it provide a new method for integrated multisensor simulation under a united environment. In the past, most simulation and animati...
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ISBN:
(纸本)0780336763
Simulation under Virtual Reality is the front edge of simulation technology. And also, it provide a new method for integrated multisensor simulation under a united environment. In the past, most simulation and animation systems utilized in robotics, which are concerned with simulation of the robot and its environment without simulation of sensors, have difficulty in handling robots that utilize sensory feedback in their operation. Currently, navigation and planning heavily depended on perception has already been mainstream in robotics. Sensor fusion plays a important role in navigation. So, it is important to do research on simulators which deal with multisensor, integrated robot simulation. In this paper, we present a system, which is integrated multisensor feedback under virtual reality, and describe the system architecture and dynamic behavior simulation model. Meanwhile, we also give the difference of simulation between VR system and general 2D system. We choice the mobile robot THMRIII as original source, and give it dynamic simulation model. In order to simulate the uncertainty of ultrasonic sensor, we identify three kinds of uncertainty, and give a ultrasonic sensor model based on fuzzy theory. The sensor simulation algorithm is presented. At the end of this paper, we conclude with discussion of sensor fusion under 3D visualized integrated environment.
This paper discusses a rough set approach for evaluating solutions of scheduling problems. Algorithms for solving scheduling problems are planners and the scheduling problems are modelled as constraint satisfaction pr...
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This paper discusses a rough set approach for evaluating solutions of scheduling problems. Algorithms for solving scheduling problems are planners and the scheduling problems are modelled as constraint satisfaction problems. Conventional approach for the analysis of algorithms often focuses on the time and representational complexities, and assumes an identical cost on all operations. The proposed rough set approach augments conventional approaches for the analysis of algorithms in two ways: 1) it permits the consideration of different costs arising from different operations; and 2) it allows one to define a new utility for a complexity analysis.
In this paper, the intelligent mobile robot key techniques are introduced, such as architecture of intelligent mobile robot, path planning and its simulation techniques, transducer and multisensor fusion techniques, d...
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ISBN:
(纸本)0780331044
In this paper, the intelligent mobile robot key techniques are introduced, such as architecture of intelligent mobile robot, path planning and its simulation techniques, transducer and multisensor fusion techniques, design and implement of intelligent mobile robot, vision subsystem and information reduced techniques, research of ''perception - action'' behavior and application of fuzzy control, etc.. A real outdoor mobile robot THMR-III (TsingHua Mobile Robot) that we developed has demonstrated road following, obstacle avoiding, branch road distinguishing and navigation, cross-country and target following at average speed 3.0 m/s.
Bug fixing holds significant importance in software development and maintenance. Recent research has made substantial strides in exploring the potential of large language models (LLMs) for automatically resolving soft...
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Bug fixing holds significant importance in software development and maintenance. Recent research has made substantial strides in exploring the potential of large language models (LLMs) for automatically resolving software bugs. However, a noticeable gap in existing approaches lies in the oversight of collaborative facets intrinsic to bug resolution, treating the process as a single-stage endeavor. Moreover, most approaches solely take the buggy code snippet as input for LLMs during the patch generation stage. To mitigate the aforementioned limitations, we introduce a novel stage-wise framework named PATCH. Specifically, we first augment the buggy code snippet with corresponding dependence context and intent information to better guide LLMs in generating the correct candidate patches. Additionally, by taking inspiration from bug management practices, we decompose the bug-fixing task into four distinct stages: bug reporting, bug diagnosis, patch generation, and patch verification. These stages are performed interactively by LLMs, aiming to simulate the collaborative behavior of programmers during the resolution of software bugs. By harnessing these collective contributions, PATCH effectively enhances the bug-fixing capability of LLMs. We implement PATCH by employing the powerful dialogue-based LLM ChatGPT. Our evaluation on the widely used bug-fixing benchmark BFP demonstrates that PATCH has achieved better performance than state-of-the-art LLMs.
The Cross-lingual Dependency Parsing (XDP) task poses a significant challenge due to the differences in dependency structures between training and testing languages, known as the out-of-distribution (OOD) problem. Our...
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The Cross-lingual Dependency Parsing (XDP) task poses a significant challenge due to the differences in dependency structures between training and testing languages, known as the out-of-distribution (OOD) problem. Our research delved into this issue in the XDP dataset by selecting 43 languages from 22 language families. We found that the primary factor of the OOD problem is the unbalanced length distribution among languages. To address the impact of the OOD problem, we propose deep stable learning for Cross-lingual Dependency Parsing (SL-XDP), which utilizes deep stable learning with a feature fusion module. In detail, we implemented five feature fusion operations for generating comprehensive representations with dependency relations and the deep stable learning algorithm to decorrelate dependency structures with sequence length. Our experiments on Universal Dependencies have demonstrated that SL-XDP can lessen the impact of the OOD problem and improve the model generalization among 21 languages, with a maximum improvement of 18%.
The 2010 Pacific-Rim Conference on Multimedia (PCM 2010) was held in Shanghai at Fudan University, during September 21–24, 2010. Since its inauguration in 2000, PCM has been held in various places around the Pacific ...
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ISBN:
(数字)9783642157028
ISBN:
(纸本)9783642157011
The 2010 Pacific-Rim Conference on Multimedia (PCM 2010) was held in Shanghai at Fudan University, during September 21–24, 2010. Since its inauguration in 2000, PCM has been held in various places around the Pacific Rim, namely Sydney (PCM 2000), Beijing (PCM 2001), Hsinchu (PCM 2002), Singapore (PCM 2003), Tokyo (PCM 2004), Jeju (PCM 2005), Zhejiang (PCM 2006), Hong Kong (PCM 2007), Tainan (PCM 2008), and Bangkok (PCM 2009). PCM is a major annual international conference organized as a forum for the dissemination of state-of-the-art technological advances and research results in the fields of theoretical, experimental, and applied multimedia analysis and processing. PCM 2010 featured a comprehensive technical program which included 75 oral and 56 poster presentations selected from 261 submissions from Australia, Canada, China, France, Germany, Hong Kong, India, Iran, Italy, Japan, Korea, Myanmar, Norway, Singapore, Taiwan, Thailand, the UK, and the USA. Three distinguished researchers, Prof. Zhi-Hua Zhou from Nanjing University, Dr. Yong Rui from Microsoft, and Dr. Tie-Yan Liu from Microsoft Research Asia delivered three keynote talks to the conference. We are very grateful to the many people who helped to make this conference a s- cess. We would like to especially thank Hong Lu for local organization, Qi Zhang for handling the publication of the proceedings, and Cheng Jin for looking after the c- ference website and publicity. We thank Fei Wu for organizing the special session on large-scale multimedia search in the social network settings.
The 2010 Pacific-Rim Conference on Multimedia (PCM 2010) was held in Shanghai at Fudan University, during September 21–24, 2010. Since its inauguration in 2000, PCM has been held in various places around the Pacific ...
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ISBN:
(数字)9783642156960
ISBN:
(纸本)9783642156953
The 2010 Pacific-Rim Conference on Multimedia (PCM 2010) was held in Shanghai at Fudan University, during September 21–24, 2010. Since its inauguration in 2000, PCM has been held in various places around the Pacific Rim, namely Sydney (PCM 2000), Beijing (PCM 2001), Hsinchu (PCM 2002), Singapore (PCM 2003), Tokyo (PCM 2004), Jeju (PCM 2005), Zhejiang (PCM 2006), Hong Kong (PCM 2007), Tainan (PCM 2008), and Bangkok (PCM 2009). PCM is a major annual international conference organized as a forum for the dissemination of state-of-the-art technological advances and research results in the fields of theoretical, experimental, and applied multimedia analysis and processing. PCM 2010 featured a comprehensive technical program which included 75 oral and 56 poster presentations selected from 261 submissions from Australia, Canada, China, France, Germany, Hong Kong, India, Iran, Italy, Japan, Korea, Myanmar, Norway, Singapore, Taiwan, Thailand, the UK, and the USA. Three distinguished researchers, Prof. Zhi-Hua Zhou from Nanjing University, Dr. Yong Rui from Microsoft, and Dr. Tie-Yan Liu from Microsoft Research Asia delivered three keynote talks to the conference. We are very grateful to the many people who helped to make this conference a s- cess. We would like to especially thank Hong Lu for local organization, Qi Zhang for handling the publication of the proceedings, and Cheng Jin for looking after the c- ference website and publicity. We thank Fei Wu for organizing the special session on large-scale multimedia search in the social network settings.
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