Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems最新文献_第10页

A maximum likelihood algorithm for solving the correspondence problem in tri-aural perception 求解三耳感知对应问题的最大似然算法

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398414

H. Peremans

引用次数: 13

Fusion technologies for drug interdiction 用于毒品拦截的融合技术

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398421

C. Chong, M. Liggins

引用次数: 14

Fault diagnosis of plant systems using immune networks 基于免疫网络的植物系统故障诊断

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398475

A. Ishiguro, Yuji Watanabe, Y. Uchikawa

引用次数: 48

Learning the expected utility of sensors and algorithms 学习传感器和算法的预期效用

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398401

J. Lindner, R. Murphy, Elizabeth Nitz

引用次数: 22

A frequency response method for multi-sensor high-speed navigation systems 多传感器高速导航系统的频率响应方法

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398478

S. Cooper, H. Durrant-Whyte

引用次数: 25

Belief formation from observation and belief integration using virtual belief space in Dempster-Shafer probability model 邓普斯特-谢弗概率模型中基于观察的信念形成与虚拟信念空间的信念整合

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398429

T. Matsuyama

{"title":"Belief formation from observation and belief integration using virtual belief space in Dempster-Shafer probability model","authors":"T. Matsuyama","doi":"10.1109/MFI.1994.398429","DOIUrl":"https://doi.org/10.1109/MFI.1994.398429","url":null,"abstract":"Integrating uncertain information from multiple sources is a key technology to realise reliable AI systems. The Dempster-Shafer probability model (DS model) provides a useful computational scheme for the integration. In this paper, the author proposes two algorithms for belief formation and integration based on the DS model. The first algorithm is for computing a basic probability assignment function based on similarity measures between observed data and object categories. The soundness of the algorithm is shown using mathematical relations between several fuzzy measures. Then, the author proposes a new algorithm for integrating multiple beliefs (i.e, basic probability assignment functions). Using this algorithm, the author can solve a controversial problem in the DS model about how to combine partially conflicting beliefs. That is, with the proposed algorithm, the author can smoothly integrate multiple beliefs even if they are partially/totally conflicting. From a computational viewpoint, moreover, the belief integration by the proposed algorithm can be implemented very efficiently.<<ETX>>","PeriodicalId":133630,"journal":{"name":"Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems","volume":"2010 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129126485","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: 18

Haptic recognition system with sensory integration and attentional perception 具有感觉统合和注意知觉的触觉识别系统

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398441

Y. Sakaguchi, K. Nakano

{"title":"Haptic recognition system with sensory integration and attentional perception","authors":"Y. Sakaguchi, K. Nakano","doi":"10.1109/MFI.1994.398441","DOIUrl":"https://doi.org/10.1109/MFI.1994.398441","url":null,"abstract":"The authors constructed a haptic recognition system which discriminates feel of touch based on the principles of sensory integration and attentional perception. The system is equipped with several sensors and can push and rub the object's surface with several values of force and speed. It integrates the sensory information iteratively by selecting appropriate sensors and measurement conditions according to the proceeding of the recognition. The algorithms of sensory integration and of attentional perception are realized by Bayes inference and by an iterative experimental design based on an information criterion, respectively. The experimental result shows that the system can discern a subtle difference in feel of touch. It is also proved that the system selects appropriate sensors and conditions according to the situation, that is, the attentional perception algorithm realizes good recognition accuracy with fewer observations. In addition, it is shown that the characteristics used in the system correspond well to those human beings utilize in haptic perception. These results suggest that the constructed system is a faithful model for the human haptic mechanism.<<ETX>>","PeriodicalId":133630,"journal":{"name":"Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117346365","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: 3

A reflexive navigation algorithm for an autonomous mobile robot 自主移动机器人的自反导航算法

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398445

J. Vandorpe, H. Van Brussel

引用次数: 20

Positioning by tree detection sensor and dead reckoning for outdoor navigation of a mobile robot 基于树检测传感器和航位推算的移动机器人室外导航定位

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398392

S. Maeyama, A. Ohya, S. Yuta

引用次数: 57

Implementation of an intelligent roving robot using multiple sensors 采用多传感器的智能粗纱机器人的实现

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398378

S. Hwang, B.P. Kintigh

引用次数: 2