Feed Your Mind - A Tutorial On Deep Learning (ISCAS 2022 Invited Talk)
Abstract: Learning is the acquisition of knowledge or skills through experience, study, or being thought. Machine learning is the automated discovery of rules to execute a data processing task given examples of what is expected. Deep Learning is a sub-field of Machine Learning in which transformations are applied to input data using multiple processing layers. This tutorial is organized as follows. Part 1 introduces Machine Learning and Deep Learning, Deep learning models, model training, and how to build and test models using readily available open-source tools. Part 2 introduces Convolutional Neural Networks. Various examples of applications and use cases are provided throughout the tutorial.
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Xavier Elenes of Silicon Labs
A Tutorial On Deep Learning
Biography:
Javier Elenes received Bachelor of Science and Master of Science degrees in electrical engineering from Drexel University in 1996. He joined Silicon Labs in 2004 where he currently serves as Distinguished Engineer. From 2004 until 2016 he led the development and implementation of various digital signal processing algorithms for receiver synchronization, signal detection, channel estimation, adaptive equalization, and antenna diversity. From 2016 until 2019 he focused on security, side-channel analysis, device hacking and countermeasures. Since 2019 he has been working on Deep Learning models and architectures for embedded devices. He holds 34 U.S. patents in signal processing, receiver architectures, and embedded security.
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