UTS Tech Festival (June 20 – July 01, 2022 )is a two weeks festival of events, showcases, hackathons, workshops, masterclasses, seminars, competitions, industry-student engagement and much more! Our goal is to bring together students, academics and industry to foster learning, inspiration, share ideas and promote innovation.

We’re excited to welcome you to our campus for theHands-on MATLAB workshop on Deep Learning with Imageswhich is part of theUTS Tech Festival 2022!

About:

Please join MathWorks on 28th June 2022 and learn how to get started with MATLAB for Deep Learning with Images. In this hands-on workshop, we will introduce you to fundamentals of Deep Learning with Images. You’ll have the opportunity to try out specific examples using MATLAB tools. The hands-on component of the workshop will be run via MATLAB Online – so attendees do NOT need to have MATLAB locally installed on their computers.

Highlights:

Learn the Deep Learning image classification workflow in MATLAB
1. Image Data management
2. Network assembly, training
3. Experiment management
Create a Convolution Neural Network (CNN) from scratch
1. Programmatically and using APPs
Explore how to access and adjust pretrained models (transfer learning)
Explore how to evaluate the network and improve its accuracy

Who should attend:

The session is aimed at students and academics who are interested in getting started with MATLAB for Deep Learning image classification applications.

Date, Location, Venue:

Date:Tuesday, June 28, 2022,
Time : 9.30am-12.30pm
Venue: Building 11, Level 00, Room: 405, UTS City Campus.Details will be available on the confirmation email as well.

Prework:

Attendees will need to bring their own laptops (MATLAB does NOT need to be installed)
Attendees will need to have a MathWorks account associated with the UTS MATLAB Campus License.
See the following FAQ for instructions on how to create a MathWorks account
https://www.mathworks.com/videos/create-a-mathworks-account-using-a-matlab-portal-1600159919958.html

Presenter:

Bradley Horton is a member of the Academic Customer Success team at MathWorks, helping faculty members better utilize MATLAB and Simulink for education and research. Bradley has supported and consulted for clients on projects in process control engineering, power systems simulation, military operations research, and earthquake impact modelling. Before joining MathWorks, Brad spent 5 years as a systems engineer with the Defence Science & Technology Organization (DSTO) working as an operations research analyst. Bradley holds a B.Eng. in Mechanical engineering and a B.Sc. in Applied mathematics.

Organizers:

Intelligent Drone Lab (iDL),AAII, and Faculty of Engineering and IT.

Question?

For inquiries please contact us at : Nabin.Sharma@uts.edu.au