2009 IEEE International Conference on Intelligent Computing and Intelligent Systems最新文献_第7页

LQG optimum controller design and simulation base on inter model control theory 基于模型间控制理论的LQG最优控制器设计与仿真

2009 IEEE International Conference on Intelligent Computing and Intelligent Systems Pub Date : 2009-12-28 DOI: 10.1109/ICICISYS.2009.5358234

Q. Jin, S. Ren, Ling Quan

引用次数: 5

Topic indexing of spoken documents based on optimized N-best approach 基于优化n -最优方法的口语文档主题索引

2009 IEEE International Conference on Intelligent Computing and Intelligent Systems Pub Date : 2009-12-28 DOI: 10.1109/ICICISYS.2009.5357691

Lei Zhang, Jing-xin Chang, Xuezhi Xiang, Xiaosen Feng

{"title":"Topic indexing of spoken documents based on optimized N-best approach","authors":"Lei Zhang, Jing-xin Chang, Xuezhi Xiang, Xiaosen Feng","doi":"10.1109/ICICISYS.2009.5357691","DOIUrl":"https://doi.org/10.1109/ICICISYS.2009.5357691","url":null,"abstract":"For topic indexing of spoken documents, the word error rate is hopefully decreased instead of the whole sentence error rate, so the center hypothesis among the N-best results is selected as the final output in speech recognition system. Then all spoken documents can be represented as vectors with high dimensions in vector space model, which can be combined with non-negative matrix factorization or singular value decomposition to map the vector space into semantic space. Experiment results show that optimized N-best approach is more suitable to the topic indexing system than one-best method. Combined with the non-negative matrix factorization, the correct topic indexing can achieve 98.1% in optimized N-best approach, which is 0.9% higher than the one-best approach under the same condition. When the semantic space is decreased to 10, there is about 11.1% difference between these two approaches. Furthermore, compared with singular value decomposition method, non-negative matrix factorization has the advantages of better performance, faster computation speed and less storage space.","PeriodicalId":206575,"journal":{"name":"2009 IEEE International Conference on Intelligent Computing and Intelligent Systems","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115439775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Knowledge-based system for strip layout design in fineblanking 基于知识的精密落料带材排样设计系统

2009 IEEE International Conference on Intelligent Computing and Intelligent Systems Pub Date : 2009-12-28 DOI: 10.1109/ICICISYS.2009.5358146

H. Xiang, X. Zhuang, Zhen Zhao

引用次数: 5

ADOA / TDOA combined positioning with dual-antenna over fading channel 衰落信道下双天线ADOA / TDOA组合定位

2009 IEEE International Conference on Intelligent Computing and Intelligent Systems Pub Date : 2009-12-28 DOI: 10.1109/ICICISYS.2009.5358255

Xiaonan Li, Lijuan Bai, Jing Li

引用次数: 0

Building recognition from aerial images combining segmentation and shadow 结合分割和阴影的航拍图像构建识别

2009 IEEE International Conference on Intelligent Computing and Intelligent Systems Pub Date : 2009-12-28 DOI: 10.1109/ICICISYS.2009.5357616

Keyan Ren, Hanxu Sun, Q. Jia, Jianbo Shi

引用次数: 12

Line detection of parts using local uncertainty measure and local RHT in noised images 基于局部不确定度和局部RHT的零件线检测

2009 IEEE International Conference on Intelligent Computing and Intelligent Systems Pub Date : 2009-12-28 DOI: 10.1109/ICICISYS.2009.5357742

Ma Li, Junyong Mao, Huang Kejie

引用次数: 0

Simulation of microstructure defects creep on nickel-based superalloys by Genetic Algorithm 基于遗传算法的镍基高温合金显微组织缺陷蠕变模拟

2009 IEEE International Conference on Intelligent Computing and Intelligent Systems Pub Date : 2009-12-28 DOI: 10.1109/ICICISYS.2009.5357835

Meng I. Lei, Zhang Shu

引用次数: 1

Combining K-means and particle swarm optimization for dynamic data clustering problems 结合k -均值和粒子群算法求解动态数据聚类问题

2009 IEEE International Conference on Intelligent Computing and Intelligent Systems Pub Date : 2009-12-28 DOI: 10.1109/ICICISYS.2009.5358020

Yucheng Kao, Szu-Yuan Lee

引用次数: 42

Automated assessment of buried pipeline defects by image processing 基于图像处理的埋地管道缺陷自动评估

2009 IEEE International Conference on Intelligent Computing and Intelligent Systems Pub Date : 2009-12-28 DOI: 10.1109/ICICISYS.2009.5357617

Wu Xue-fei, Bai Hua

{"title":"Automated assessment of buried pipeline defects by image processing","authors":"Wu Xue-fei, Bai Hua","doi":"10.1109/ICICISYS.2009.5357617","DOIUrl":"https://doi.org/10.1109/ICICISYS.2009.5357617","url":null,"abstract":"Many underground water pipelines are old and approaching their service lives in a great number of cities. With the promotion of sustaining buried infrastructure, it's necessary to pay much attention on how to effectively extract defect characteristics of damaged pipelines. Detection of defects in underground pipes is a crucial step to assess the deterioration degree of pipeline for municipal operators. Based on the image processing theory, a defect feature extracting method under HSV color space is proposed in this paper. QFCM (Quick Fuzzy C-Mean clustering) segmentation arithmetic is applied to extract characteristics parameters. The proposed algorithm can identify defects from background, and the types of defects in the buried pipes can be categorized in the estimation stage. Then, different methodologies of parameters extraction are applied in different types of pipe defects, features like area, angle, length and width of defects can also be calculated. And then, a method of assessing the accuracy of feature extraction algorithm is discussed. Finally, the proposed detection approach has been experimentally tested using a group of images acquired by CCD camera from real inspection scenarios. The experimental results proved that it is feasible and effective to apply the system in feature extraction of pipe defects of the underground water-pipelines.","PeriodicalId":206575,"journal":{"name":"2009 IEEE International Conference on Intelligent Computing and Intelligent Systems","volume":"209 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114742965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Important event extraction of chinese document based on small world model 基于小世界模型的中文文档重要事件提取

2009 IEEE International Conference on Intelligent Computing and Intelligent Systems Pub Date : 2009-12-28 DOI: 10.1109/ICICISYS.2009.5357919

Shan Jian-fang, Zongtian Liu, Fu Jian-feng, Zhong Zhaoman

引用次数: 2