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    Lessons Learned from Artificial Intelligence applications in Cultural Heritage and Medicine
    瀏覽次數:日期:2020-12-11編輯:信科院 科研辦

    報告人:Francesco Piccialli,University of Naples FEDERICO II,意大利,助理教授。

    報告時間:202012月23日 (星期三) 晚上8:00 - 10:00

    報告地點:Zoom在線會議

    https://us02web.zoom.us/j/2810019605?pwd=S09LNnl5dHdXajZBbEJJOVd4TVlmUT09

    Meeting ID: 281 001 9605

    Passcode: HNU2020

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    報告摘要:In recent years, there has been an exponential growth in researchers’ use of the term “Data Science” to describe the interdisciplinary field of collecting, drawing inference from, and acting on data. We are facing an evolution in the way traditional Business Intelligence (BI) operations are conducted, bringing it closer to Data Science. In applying innovative techniques to old problems, however, we must be careful to distinguish between those that are advances in Machine and Deep Learning (ML and DL) research and concrete results. DL offers the possibility to automate processes, even sophisticated ones, without having to program a computer explicitly but letting the rules and structures emerge from the available data. First, the amount of data must be sufficient to support the algorithms and distinguish the value signal from the background noise.  However, there are many possible models and approaches to accomplish this task. The choice of the most suitable models depends crucially on the type of problem and data available, and the world of research (state of the art) offers some preliminary indications in this regard.

    In this talk, we firstly discuss the application of ML techniques on IoT data collected in a Cultural Heritage framework. Behavioural data have been gathered in a non-invasive way to achieve a classification that can be exploited by cultural stakeholders in terms of medium-long term strategy and also in terms of strictly operational decisions. Then we discuss the role of Deep Learning in Medicine, also focusing on challenges and future directions. Finally, we will point out the attention on the role of Artificial Intelligence in fighting the COVID-19 pandemic, presenting an overview and the application of AI in the different phases of the pandemic.

     

    報告人簡介:Francesco Piccialli is currently Assistant Professor (tenure track) of Computer Science at the Department of Mathematics and Applications “R. Caccioppoli” (DMA) of the University of Naples Federico II (UNINA), Italy.In 2018 he took the Italian Scientific Habilitation for Associate Professorship. He received a Laurea Degree (BSc+MSc) in Computer Science and a PhD in Computational and Computer sciences from the Unviersity of Naples Federico II, Italy in 2012 and 2016, respectively.He has been Visiting Research Scholar at Chun-Ang University (CAU), Seoul, South Korea in 2017 and Visiting Professor at University of Geosciences, Beijing, China in 2019. He is also research fellow at CINI (National Interuniversity Consortium for Informatics) from 2013.He is co-founder and Scientific director of T.P.S. S.r.l., an innovative Start-up company whose mission is the development of innovative systems and services based on IoT technology for Cultural Heritage.He is the founder and Scientific director of the M.O.D.A.L. research group that is engaged in cutting-edge on novel methodologies, applications and services in Data Science and Machine Learning fields and their emerging application domains.

      

    邀請人:李肯立

     

    聯系人:陳建國

     

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