詹前隆院長 时间：2019年3月15日上午（9:00-9:20）
地点：数计学院2号楼309报告厅
元智大學資訊學院與大數據與數位匯流創新中心簡介Introduction of College of Informatics and Innovative Center for Big Data and Digital Convergence
报告人简介：
詹前隆，教授，美國威斯康辛大學麥迪遜校區決策科學博士(1995)。現任元智大學資訊管理系(所)教授兼資訊學院院長、大數據與數位匯流創新研究中心執行長。
歷任元智大学資訊管理系(所)主任、元智大学資訊長、工業工程學門大數據與資訊系統子學門規劃委員、大專院校資訊管理系所評鑑委員。
近五年研究主要在整合環境、空污、天氣與醫療健康之大數據分析，獲選教育部邁向頂尖大學優良成果，研究成果發表在國際重要期刊30篇。曾獲大專校院獎勵特殊優秀人才與第十四屆有庠傑出教授獎。
陳柏豪老師 时间：2019年3月15日上午（9:20-9:50）
題目：現代科技生活的探尋與品味A Quest for Modern Living
摘要：
The era of artificial intelligence is starting to happen now! To date, the field of artificial intelligence is more vibrant than ever and some believe that we're on the threshold of discoveries that could change human society irreversibly, for better or worse. How can we ride this wave, as ordinary developers, to the benefit of everybody? This talk will use some examples of AI in our everyday lives to demonstrate what kinds of tasks should be considering for AI development process.
报告人简介：
陈柏豪，助理教授，台北科技大学电子工程博士，主要从事多媒体巨量资料分析、巨量资料数位影像处理、多媒体串流、人机界面设计等方向研究。
陳增益老師 时间：2019年3月15日上午（9:50-10:20）
題目：於次世代運算架構實現超低耗能儲存系統Enabling Ultra Low Power Storage System for Next Generation Computing Architectures
摘要：
Lately, big data has garnered much attention from academic and industrial communities due to the explosive growth of data volume in various fields, such as social networks, internet of things, and cloud storage services. In big data area, both data warehouse as well as in-memory computing (or database) are two widely discussed topics because big data requires cost-effective and large-capacity storage devices for data warehouse, as well as high-performance system architecture (e.g., in-memory computing) for big data pro- cessing. For instance, to cost-effectively maintain big data in a data warehouse application, several vendors would apply emerging storage devices, such as 3D flash memory and shingled magnetic recording (SMR), to their storage system; however, the performance of emerging storage devices is degraded owing to a high-density design. On the other hand, in-memory computing employs emerging memory technology (e.g., phase-change memory and STT-RAM) to collaborate with DRAM so as to reduce the energy consumption of memory systems, but cause significant performance degradation. Thus, to provide cost-effective and performance-efficient memory-storage system for big data applications become an interest raising research topic.
报告人简介：
陈增益，助理教授，台湾清華大學資訊工程博士，主要从事嵌入式系統、記憶儲存系統、新興非揮發性記憶體設計、物聯網路設計等方向研究。
牛玉贞：时间：2019年3月15日上午（10:20-10:50）
报告题目: Learning for Image and Video Quality Assessment
摘要：
In the big data era for media, we need image and video quality assessment metrics to distinguish high quality media contents from low quality media contents. This talk covers some works on image and video quality assessment. Firstly, we studied what makes a professional video from the perspective of aesthetics. A professional video is good not only for its interesting story but also for its high visual quality. Secondly, we presented two professional composition rules detection algorithm. One is rule of thirds detection. The other is rule of simplicity detection. Thirdly, we proposed to learn a perceptual image quality assessment index from multiple metrics by introducing saliency analysis, masking effect, etc. Lastly, we presented a color consistency assessment index based on color contrast similarity and color value differences.
报告人简介
Dr. Yuzhen Niu, now is a full professor of Fuzhou University, China, member of IEEE, ACM and CCF, AC member of CCF YOCSEF-Xiamen. Yuzhen Niu received her BS and PhD in Computer Science from Shandong University, Jinan, China, in 2005 and 2010, respectively. She was a visiting student with the Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI. She was a Post-Doctoral Researcher with the Department of Computer Science, Portland State University, Portland, OR. She is currently a Minjiang Distinguished Professor with the College of Mathematics and Computer Science, Fuzhou University, China. Her current research interests include computer vision, multimedia, machine learning, and computer graphics.
郑相涵 时间：2019年3月15日上午（10:50-11:20）
报告题目：基于区块链的数字资产安全管理
摘要：数字资产的安全、协同、可信管理是大数据流通与交易的基石,也是区块 链安全生态系统研究的重要方向。 面向大数据安全领域,针对数据在存储、迁移、流通、交易过程面临的不可信、不可管、不可控等核心安全缺陷,基于区块链,软件定义网络和协同计算等核心技术手段,给出实现数据分层、协同管理的安全理论模型与具体方案,打造数据分层管理与协同计算平台,为数字资产的大规模可信流通与交易提供基础保障。
报告人简介：
郑相涵，福州大学研究员。毕业于挪威Agder大学信息通信技术系（ICT），获网络与系统安全博士学位（2011.07）；现任福州大学网络工程与信息安全系副主任，福州大学智能制造仿真研究院副主任，福州大学物联网联合研发中心副主任（2011-2016），IEEE云计算学会（IEEE Cloud Computing Initiative）理事，IEEE区块链（IEEE Blockchain Initiative）学会理事，中国计算机学会会员代表，CCF YOCSEF福州分论坛副主席，担任IEEE TCC、JCC等云计算知名期刊客座主编，CloudCom-Asia 2013-2018, MAWAI 2015, I-Cloud等国际学术会议主席。近年来主持国家、省部级项目11项；授权发明专利12项，软件著作权31项，获福建省科学技术奖一等奖1项，三等奖2项；出版英文专著2部，正式发表各类学术论文60余篇。
刘文犀 时间：2019年3月15日上午（11:20-11:50）
报告题目：Adaptive visual tracking, multi-agent navigation, and medical image segmentation
摘要：This presentation introduces the recent progresses of our research in visual tracking, multi-agent navigation, and medical image segmentation, respectively. First, we propose a deformable convolutional tracking method that adaptively captures the motion of the deformable object. Second, we introduce a novel multi-agent navigation method that models the collision avoidance behavior that adapts to different scenarios. Last, we apply the reinforcement learning to medical image to learn the policy for adaptive scaling local patch sampling.
报告人简历
刘文犀，数学与计算机科学学院副教授，硕士生导师，2015年加入认知系统与信息处理实验室。2014年于香港城市大学计算机科学系获得博士学位。研究兴趣包括基于视觉的人群运动分析、目标跟踪、图像分割、多机器人避障等。
