Diving into Deep Learning:

From Concept to Embedded Deployment

 26 June 2019 | 08:30am-12:30pm | @Marquis Events Place, BGC, Manila

 

*****short introduction

Date: 26 June 2019 (Wednesday)

Time: 08:30am - 12:30pm

Venue: The Marquis Events Place, BGC, Manila

Agenda

Duration

0830-0900 am

0900-0915 am

0915-1015 am

1015-1030 am

1030-1130 am

1130-1200 pm

1200-1230 pm

Session

Registration

 

Welcome Speech

By Ian Alferez, Senior Application Engineer Team Leader (Singapore & Philippines)

Demystifying Deep Learning

By Alfred Orquia, Application Engineer

Coffee Break

Embedded Deployment of Deep Learning Networks

By Ian Alferez, Senior Application Engineer Team Leader (Singapore & Philippines)

Q&A

Lunch Buffet & Networking

*The agenda may be subject to changes.

Synopsis

Demystifying Deep Learning

By Alfred Orquia, Application Engineer

Deep learning can achieve state-of-the-art accuracy for many tasks considered algorithmically unsolvable using traditional machine learning, including classifying objects in a scene or recognizing optimal paths in an environment. Gain practical knowledge of the domain of deep learning and discover new MATLAB® features that simplify these tasks and eliminate the low-level programming. From prototype to production, you’ll see demonstrations on building and training neural networks and hear a discussion on automatically converting a model to CUDA® to run natively on GPUs.

Unlocking the power of Machine Learning with Engineering Data

By Ian Alferez, Senior Application Engineer Team Leader (Singapore & Philippines)

Learn how to use MATLAB® for designing, developing, and deploying computer vision and deep learning applications on NVIDIA® Tesla® GPUs or Tegra® system-on-chips, whether on your local machine, in a cluster, or on embedded systems, including NVIDIA Jetson™ TK1/TX1/TX2 and DRIVE™ PX platforms. The workflow starts with algorithm design in MATLAB. The deep learning network is defined in MATLAB and is trained using GPU and parallel computing support for MATLAB, either on the desktop computer, a local compute cluster, or in the cloud. Then, the trained network is augmented with traditional computer vision techniques and the application is verified in MATLAB. Finally, a compiler automatically generates portable and highly optimized CUDA® code from the MATLAB algorithm, which is then implemented on the Tegra platform using cross-compilation. The execution speed of the auto-generated CUDA code is ~2.5x faster than Apache MXNet™, ~5x faster than Facebook Caffe2, ~7x faster than Google™ TensorFlow™, and comparable to an optimized TensorRT™ implementation.

Speaker Profile

Ian M. Alferez is the Senior Application Engineer at TechSource Systems. He specializes in in the field of embedded system (embedded coder configuration), data analytics (Machine Learning) and technical computing with MATLAB/Simulink. He holds a Bachelor of Science in Electronics and Communication Engineering from the University of San Carlos in Cebu, Philippines. Before joining Techsource Asia, he worked as a Software Development Engineer at Lear Corporation where he refined his skills in Model Based Design with regards to the Verification and Validation Workflow and Embedded Software / Hardware. 

 

He has built his forte in Process Automation with MATLAB, Production Code Customization, Optimization and Generation with Embedded Coder, MATLAB/Simulink Algorithm for Auto Code Generation and Hardware Target Deployment, Customizing the Auto Test Generation / Property Proving with Simulink Design Verifier.

Alfred Loue F. Orquia is an Application Engineer at TechSource. He graduated in 2018 with a degree of Electronics and Communications Engineering at De La Salle University in Manila, Philippines. Later that year, he was able to pass the licensure examination for ECE. He has also received the award for Best Undergraduate Research for his team’s study on implementation of sliding mode controller on an autonomous quadcopter in which, the research paper has been published at the 2018 International Journal of Automation and Smart Technology.

 

In 2019, he joined TechSource Systems as an Application Engineer. Currently, he is establishing his expertise in Data Analytics particularly in Deep Learning and Transfer Learning using the MATLAB software. 

Venue

The Marquis Events Place

 3rd Floor Marquis Building

34th Street, Rizal Drive

Bonifacio Global City, 1634 Taguig

Tel: (02) 663 7487; (02) 663 7438

 

This seminar is free, but registration is required.