https://www.fst.um.edu.mo/wp-content/uploads/2020/05/sem20181126_01.jpg
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Instructors/Speakers Prof. Honghai LIU University of Portsmouth UK Abstract It requires innovative technologies and theoretical foundation of sensing and analytics as increasing complexity of modern systems with humans involved actively. The state of the art in human machine interface is largely dominant by solutions that are ad-hoc and application dependent. This talk attempts to summarize challenges for sensing and analytics from the perspective of human-machine systems, and presents a computational framework aiming at anchoring behaviors to hardcoded features. Two projects will be introduced to showcase the framework: human hand skill transfer and interaction with children with autism spectrum disorders. The talk will conclude with comments on open issues and challenges in human-machine systems. Biography Honghai Liu received his Ph.D from ... |
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Instructors/Speakers Prof. Xiaoli HUANG Deputy Chief Engineer of the Electric Power Planning and Engineering Institute (National Electric Power Planning and Research Center) Director of the Smart Grid Department, and Professor-level Chartered Engineer Abstract Energy is essential for human activities and is one of the main driving forces for the development of the world economy. Every major advancement in human civilization is accompanied by reforms in energy. Nowadays, the development of energy industry faces new challenges. The large-scale consumption of fossil resources has brought serious threats to global climate environment. Environmental pollution problems caused by improper development and use of energy are becoming more and more severe. The increasing energy consumption makes the contradiction between energy shortage and social development more ... |
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Instructors/Speakers Prof. He-Qing MU Associate Professor School of Civil Engineering and Transportation South China University of Technology Guangzhou China Abstract Probability distribution modelling of data is an important task in science and engineering. This research attempts to conduct probability distribution modelling of univariate and multivariate data. The first part introduces the theories of the traditional Bayesian inference and the Bayesian Network for probability distribution modelling. The second part introduced the structural health monitoring system of the Xinguang Bridge, which is a three-span half-through arch bridge with the mid span of 428 m, two side spans of 177 m each, and width of 37.62 m, over the Pearl River of Guangzhou City of China. The third part is devoted to the ... |
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Instructors/Speakers Prof. Xiaolin WU IEEE Fellow McMaster University Canada Abstract Subitizing, or the sense of small natural numbers, is an innate cognitive function of humans and primates; it responds to visual stimuli prior to the development of any symbolic skills, language or arithmetic. Given successes of deep learning (DL) in tasks of visual intelligence and given the primitivity of number sense, a tantalizing question is whether DL can comprehend numbers and perform subitizing. But somewhat disappointingly, extensive experiments of the type of cognitive psychology demonstrate that the examples-driven black box DL cannot see through superficial variations in visual representations and distill the abstract notion of natural number, a task that children perform with high accuracy and confidence. The failure is ... |
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Instructors/Speakers Prof. Raymond Yiu Keung LAU Department of Information Systems City University of Hong Kong Abstract With the rise of the Social Web, it is increasingly more popular for investors to express their feelings about firms and products on online social media. Though previous studies have examined the relationship between investors’ sentiments captured in texts (e.g., online news articles) and corporate credit ratings, there is a research gap in terms of studying the relationship between investors’ emotions captured in multimodal social postings and corporate credit ratings. By drawing upon the appraisal theory and the notion of affect-as-information, this study aims to fill the current research gap by examining the influence of investors’ emotions (e.g., trust, joy, and anger) captured in ... |
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Instructors/Speakers Dr. Guilherme RAMOS Ph.D. (2018) Information Security at Instituto Superior Técnico Lisbon, Portugal Abstract In this work, we propose to advance in the field of information security in the areas of ranking systems (RS) and control systems, using ideas from the area of information theory. First, we propose a RS that groups users based on their preferences, introducing similarity measures. The system presents possibly distinct rankings for the same product in different user groups. Besides presenting more personalized rankings to users, it is a system more resistant to attacks than the state-of-the-art. We then explore the effect of bribing in reputation-based RS, in the usual scenario (a ranking for each product) and in the scenario we proposed. We find ... |
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Instructors/Speakers Prof. Raymond WONG School of Computer Science & Engineering University of New South Wales, Sydney Australia Abstract Due to the increasing computation power and availability of big text data, text analysis research, such as text mining, natural language processing, and sentiment analysis, has drawn significant attention from both research and industry communities. This seminar presents and summarizes our recent research findings in the area of text analysis, and shares our experience in several related applications. Biography Raymond Wong is an Associate Professor at the School of Computer Science & Engineering, University of New South Wales, Sydney, Australia. From 2005-2011, he founded and led the Data Management Program at NICTA (the largest ICT organization in Australia), and was a Visiting ... |
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https://www.fst.um.edu.mo/wp-content/uploads/2020/06/sem20190103_01.jpg |
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Instructors/Speakers Prof. Linlin SHEN Shenzhen University Shenzhen China Abstract In this talk, I will mainly introduce deep learning and its applications in face recognition, analysis and translation. The history of face recognition using hand-crafted features and deep neural networks will be firstly briefed. Publicly available face datasets for both training and testing will be introduced. The most recent progress about the performance of facial recognition algorithms and their real applications will be followed. The methodologies to address face spoofing and classification of facial attributes including age, gender and expressions will be explored. Finally, the progress about face translation using GAN, pix2pix, starGAN and our proposed GAN will be presented. Biography Prof. Linlin Shen is currently a professor at Computer Science ... |
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