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英国剑桥:信息融合大会2018专题-"智能信号处理与数据挖掘"跟踪

已有 1209 次阅读 2018-3-10 16:20 |个人分类:科技动态|系统分类:博客资讯| 智能, 信号处理, 数据挖掘, 目标跟踪, 信息融合

欢迎投稿,信息融合大会2018专题-"智能信号处理与数据挖掘应用于目标跟踪”。大会2018年7月10-13号在美丽的英国剑桥举办!


information fusion - data mining - signal processing 交叉前沿!


SS11 - Intelligent Information Fusion and Data Mining for Tracking

Research on Intelligent Systems for information fusion & data mining has matured during the past years and many effective applications of this technology are now deployed such as Wearable Computing, Intelligent Surveillance, Smart City/Home-Care, Smart Grid, Web Tracking, Network Management. The rapid development of modern sensors and their application to distributed networks provide a foundation for new paradigms to combat the challenges that arise in target detection, tracking, trajectory forecasting and sensor fusion in harsh environments with poor prior information. For example, the advent of large-scale/massive sensor systems provides very informative observation, which facilitates novel perspectives based on data clustering and model learning to deal with false alarms and misdetection, given little knowledge about the objects, sensors and the background. Sensor data fitting and regression analysis provide another unlimited means to utilize the unstructured context information such as “the trajectory is smooth” for continuous-time trajectory estimation and forecasting. As such, the sensor community has the interest in novel information fusion & data mining methods coupling traditional statistical techniques for substantial performance enhancement, especially for challenging problems that make traditional approaches inappropriate.

This special session aims to assemble and disseminate information on recent, novel advances in intelligent systems, information fusion & sensor data mining techniques and approaches, and promote a forum for continued discussion on the future development. Both theoretical and practical approaches to address the problems in this area are welcome.



IMPORTANT DEADLINES

Full paper submission Deadline extended to 15 March 2018




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