Description of the Course
This workshop provides a comprehensive, hands-on introduction to deep learning techniques for signal classification using Convolutional Neural Networks (CNNs). The workshop begins with data preparation and covers how to import and label signals using tools like the Signal Labeler app. Participants will then preprocess signal data and convert time-series signals into scalograms to train the CNN model. The attendees will learn to configure the layers in a CNN, train CNN, and apply transfer learning to enhance signal classification performance. Finally, the participants will learn methods to evaluate and improve model accuracy and efficiency.
Profile of the Instructor(s)
Ms Shanthi is an experienced educator and online content developer at MathWorks, specializing in MATLAB for signal processing. She holds a master’s degree in Signal Processing. Shanthi’s professional interests span across subjects including Digital Signal Processing, Image Processing, Neural Networks, and Wireless Communication. Her scholarly contributions include publications in international journals on topics such as Video Compression Standards and their implementation in MATLAB and Background Subtraction Techniques in Image Processing. She started her career by training engineering graduates and has developed learning content for specialization courses using instructional design principles. At MathWorks, she creates online learning content related to MATLAB for signal processing and AI.
Ms Sragdhara is an online content developer at MathWorks focused on developing Simulink-based learning content. She holds a PhD degree in Control Systems. Her research areas include robust control, multi-rate control, cooperative control of multi agent systems, decentralised control, and control of cyber physical systems. She has published papers in international journals and conferences in the domain of her research. She is also an AI enthusiast and is currently exploring the applications of machine learning and deep learning in the areas of signal and image processing and developing course content.
Eligibility Criteria & Intended Audience
Intended Audience:
Engineering Students, Researchers, and industry professionals working on Signal Processing and AI Applications.
Eligibility :
Any Undergraduate or Masters Engineering Students, Researchers and Industry professionals working on Signal Processing and AI Applications can attend this workshop.
Prerequisites:
Basic MATLAB knowledge, Basics of Signal processing.
Certification
Certificates will be provided to all the participants who attends the workshop
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