Deep Learning for Signals and Time Series

Overview

Deep Learning is a key technology driving the current Artificial Intelligence (AI) megatrend. You may have heard of some mainstream applications of deep learning, but how many of them would you consider applying to your engineering and science applications? MathWorks developers have purpose-built MATLAB's deep learning functionality for engineering and science workflows. We understand that success goes beyond just developing a deep learning model. 

DL Signals and time series

Ultimately, models need to be incorporated into an entire system design workflow to deliver a product or a service to the market.

 

Topics include:

  • Extract the set of acoustic features that will be used as inputs to the LSTM Deep Learning network

  • Train LSTM network to classify multiple modes of operation

  • Generating optimized native embedded code​

 

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Date:  15 June  2021

Time: 15:00 PM (GMT+8)

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Speaker

Siti Safwana


Siti Safwana is an Senior Application Engineer at TechSource Systems. She is specialized in the field of image processing, computer vision, machine learning, and deep learning with MATLAB. She helps various customers across different industries on projects such as real-time object recognition, manufacturing defect objects detection using Deep Learning and Computer Vision, data forecasting analytics, and multiple image processing project-based.
She additionally holds an HRDF Train-The-Trainer (TTT) certificate and trained in official MathWorks training programs like MATLAB Fundamental, Image Processing, and Machine Learning. She teaches and covers ASEAN region such as Malaysia and Philippines.
Siti Safwana holds an M.Eng in Science in Electronics from Universiti Teknikal Malaysia Melaka (UTeM) and currently pursuing her Ph.D. in Science in Electronic researching computer vision field in the domain of depth/disparity map and 3D reconstruction using Artificial Intelligence at UTeM under the department of Faculty of Electronic and Computer Engineering.


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