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EDA Group

ECG signal denoising method based on deep convolutional network

azienda Thesis in external company    


keywords MACHINE LEARNING, ARTIFICIAL NEURAL NETWORKS, OPTIMIZATION, INTELLIGENT TRANSPORTATION SYSTEMS

Reference persons ALESSANDRO ALIBERTI, EDOARDO PATTI

External reference persons Mattia Tarchini Bojczuk

Research Groups DAUIN - GR-06 - ELECTRONIC DESIGN AUTOMATION - EDA, EDA Group, ELECTRONIC DESIGN AUTOMATION - EDA, Energy Center Lab, GR-06 - ELECTRONIC DESIGN AUTOMATION - EDA, ICT4SS - ICT FOR SMART SOCIETIES

Thesis type APPLIED RESEARCH

Description In the context of a company project, the student will investigate the state of the art of bio-signal denoising techniques (i.e., ECG), with a focus on techniques based on deep convolutional networks, to develop innovative methodologies by leveraging the latest Machine Learning techniques

Required skills python


Deadline 17/01/2025      PROPONI LA TUA CANDIDATURA