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on
1
Introduction
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Scenario
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Why is this scenario realistic
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Measurement infrastructure
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Challenges
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The problem
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The solution
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Low resolution to high resolution
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GAN framework
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Discriminator framework
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Generator framework
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Discriminator
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Validate
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Results
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Example
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Peak detection
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Making sense of other processes
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Coffee days
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Conclusion
Description:
Explore the application of deep learning in deciphering mobile network traffic patterns in this 20-minute talk by Paul Patras from Edinburgh. Delve into the challenges of urban data analysis, focusing on smart city initiatives and the use of advanced machine learning techniques. Learn about measurement infrastructure, the proposed GAN framework for enhancing data resolution, and practical applications such as peak detection. Gain insights into how this research contributes to building safer and more resilient urban systems, addressing the growing demands of rapidly expanding cities in the 21st century.

Making Sense of Mobile Network Traffic Using Deep Learning - Paul Patras, Edinburgh

Alan Turing Institute
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