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ICCC'20

September 07 - 11

11th International Conference on Computational Creativity

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109

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92

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1

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Christian Guckelsberger

Queen Mary University

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Andrea Cavallaro · ICPRAM 2020

Privacy-preserving Machine Learning for Multimedia Data

The pervasiveness of cameras and associated sensors is offering incredible opportunities to improve services and our quality of life, while however simultaneously posing important societal challenges. Enabling multimedia applications and services while protecting privacy is a major challenge that must be addressed to adapt to increased capabilities of classifiers and changing demands from users. In this talk I will cover new privacy preserving analytical frameworks for single and multimedia sensor data, such as images, videos, audio, as well as accelerometer and gyroscope data. Specifically, I will discuss as applications image sharing in social media, mobile-based health, and video capturing, and talk about desirable (and undesirable) inferences from various types of data.

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Carey Ming-Li Chen

How to improve the quality of grant proposal review? -The exercise of responsible peer review in Taiwan

PEERE 2020 • Sep 30, 2020

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IEEE SERVICES 2020

2020 IEEE World Congress on Services

upcoming IEEE SERVICES 2020

18 — 24 October 2020

Live on Underline

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109

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92

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