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2018年5月17日第二届海外青年学者论坛bd手机版官网登录ios 分论坛预告

来源: bd手机版官网登录ios | 发表时间: 2018-05-15 | 浏览次数: 1999

时间:517(周四)9:00-11:30

  

地点:仙林校区计算机学科楼327会议室

  

报告人:卢国玉

目:Localize me Anywhere, Anytime: A Multi-task Point-Retrieval Approach

:

       Image-based localization is an essential complement to GPS localization. Current image-based localization methods are based on either 2D-to-3D or 3D-to-2D to find the correspondences, which ignore the real scene geometric attributes. The main contribution of our paper is that we use a 3D model reconstructed by a short video as the query to realize 3D-to-3D localization under a multi-task point retrieval framework. Firstly, the use of a 3D model as the query enables us to efficiently select location candidates. Furthermore, the reconstruction of 3D model exploits the correlations among different images, based on the fact that images captured from different views for SfM share information through matching features. By exploring shared information (matching features) across multiple related tasks (images of the same scene captured from different views), the visual feature's view-invariance property can be improved in order to get to a higher point retrieval accuracy. More specifically, we use multi-task point retrieval framework to explore the relationship between descriptors and the 3D points, which extracts the discriminant points for more accurate 3D-to-3D correspondences retrieval. We further apply multi-task learning (MTL) retrieval approach on thermal images to prove that our MTL retrieval framework also provides superior performance for the thermal domain. This application is exceptionally helpful to cope with the localization problem in an environment with limited light sources.

报告人简介:

Guoyu Lu is an Assistant Professor and PhD supervisor at the Chester F. Carlson Center for Imaging Science of Rochester Institute of Technology (RIT). Prior to joining RIT, he was a research scientist on autonomous driving at Ford Research and computer vision engineer at ESPN Advanced Technology Group. He finished my PhD and MS in Computer Science at the University of Delaware. Before coming to UD, he was in European Master in Informatics (EuMI) Erasmus Mundus program. He obtained Master degree in Computer Science at University of Trento and Master degree in Media Informatics at RWTH Aachen University. He also finished an academic visiting in Auckland University of Technology KEDRI group in 2012. He was a research intern at Siemens Corporate Research in Princeton and Bosch Research in Palo Alto. He finished my Bachelor degree in Software Engineering at Nanjing University of Posts & Telecommunications, with a minor in Business Administration and Management. He was the recipient of the most prestigious Frank Person Graduate Student Achievement Award at University of Delaware Computer Science Department and the winner of European Alliance for Innovation (EAI) Students Innovation Competition. He has published over 20 papers on international journals and conferences as the first author. He was the managing guest editor of the Springer Journal of Multimedia Tools and Applications. He was the area chair of the 4th Ford Global Control Conference and the organizer and leading program chair of the CVPR International Workshop on Visual Odometry and Computer Vision Applications Based on Location Clues.

  

报告人:蒙威志

目:Emerging Smartphone Security: Charging Threat and Defence

:

随着智能手机的广泛应用,其安全问题也引起了多方的关注。但是手机的充电安全往往容易被用户忽略,但同时也是一个比较新的研究领域。本报告分为两个主要部分:第一部分主要介绍现有的一些针对智能手机的充电攻击手段。第二部分主要介绍如何防范该类型的攻击,比如通过分析手机内存使用情况来监测充电阶段的异常,发现充电过程中存在的潜在危险。

报告人简介:

Weizhi Meng is currently an assistant professor in the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU), Denmark. He obtained his Ph.D. degree in Computer Science from the City University of Hong Kong (CityU), Hong Kong. Prior to joining DTU, he worked as a research scientist in Infocomm Security (ICS) Department, Institute for Infocomm Research, Singapore, and a senior research associate at CityU. He won the Outstanding Academic Performance Award during his doctoral study. He is a recipient of The HKIE Outstanding Paper Award for Young Engineers/Researchers in both 2014 and 2017, and a co-recipient of the Best Student Paper Award from NSS 2016. His primary research interests are cyber security and intelligent technology in security, including intrusion detection, smartphone security, biometric authentication, HCI security, cloud security, trust computation, malware and vulnerability analysis. He also shows a strong interest in applied cryptography.

  

  

报告人:薛磊

目:Malton: Towards On-Device Non-Invasive Mobile Malware Analysis for ART

:

       It's an essential step to understand malware's behaviors for  eveloping effective solutions. Though a number of systems have been proposed to analyze Android malware, these systems have been limited by incomplete view of inspection on a single layer. What's worse, various new techniques including packing, anti-emulator and cross-layer malicious payloads, employed by the latest malware samples further make these systems ineffective. In this paper, we propose Malton, a novel on-device non-invasive analysis platform for the new Android runtime, i.e., the ART runtime. As a dynamic analysis tool, Malton runs on real mobile devices and provides a comprehensive view of malware's behaviors by conducting multi-layer monitoring and information flow tracking, as well as efficient path exploration. We have carefully evaluated Malton using real-world malware samples. The experimental results showed that Malton is more effective than existing tools, with the capability to analyze sophisticated malware samples and provide a comprehensive view of malicious behaviors of these samples.

报告人简介:

薛磊现为香港理工大学计算机系博士后研究院,研究方向为网络安全,网络测量,移动安全和物联网安全,目前以第一作者在系统安全顶级会议USENSIX Security,顶级期刊IEEE Transactions on Information Forensics and Security, 软件工程顶级会议ICSE,计算机网络顶级会议INFOCOM 上发表学术论文,并申请美国专利和中国专利各两项,此外还受邀参加工HITCON XCON 等工业界会议并做报告,其中关于物联网安全的工作受到了台湾多家媒体报道。


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