IEEE Fellow、罗切斯特大学Gaurav Sharma教授系列学术报告通知

2019-03-12 16:27



应计算机科学与技术学院院长王亚东教授邀请,在国际合作部国际项目管理中心支持下,IEEEFellow、美国罗切斯特大学Gaurav Sharma教授即将于2019311-2019324日访问我校。访问期间将在我校开展三场学术报告。欢迎感兴趣的老师和同学参加。


报告时间:315 09:00-10:30


报告主题:Publication Etiquette and Ethics:Things You Should Know Before Submitting Your Next Paper


Publishing a research paper is usually an exciting experience for most researchers. In this excitement, it is important to not forget that the writing process for the first few manuscripts also often lays the ground for future habits. This presentation, intended for authors unfamiliar with the process of publishing a technical paper, provides a guide to established etiquette and ethics in scholarly publishing.



报告时间:315 14:00-15:30


报告主题:Imaging Arithmetic: Physics U Math > Physics + Math


For several real-world problems, signal and image processing approaches are most successful when they combine the insight offered by the physics underlying the problem with the mathematical framework and tools inherent in digital signal and image processing. Electronic imaging systems are a particularly fertile ground for problems in this class because they deal specifically with the capture of physical scenes and with the reproduction of images on physical devices. In this presentation, we highlight specific examples of problems in electronic imaging for which the combination of physical insight, mathematical tools, and engineering ingenuity leads to particularly elegant and effective solutions.



报告时间:322 14:00-15:30


报告主题:Large Scale Visual Data Analytics for Geospatial Applications

主要内容:The widespread availability of high resolution aerial imagery covering wide geographical areas is spurring a revolution in large scale visual data analytics. We present results from our recent research in this area covering three topics. First, we describe a novel method for pixel accurate, real-time registration of vector roadmaps to WAMI imagery based on moving vehicles in the scene. Next, we present a framework for tracking WAMI vehicles across multiple frames by using the registered roadmap and a new probabilistic framework that allows us to better estimate associations across multiple frames in a computationally tractable algorithm. Finally, in the third part, we highlight, how we can combine structure from motion and our proposed registration approach to obtain 3D georegistration for use in application such as change detection.


Gaurav Sharma教授


IEEE FellowSPIE Fellow、成像科学与技术学会(I&T Fellow。担任罗切斯特大学电子与计算机工程系教授、数据科学卓越中心(CoE)杰出研究员、Goergen数据科学研究所卓越中心杰出研究员。