เรียนเชิญเข้าร่วมการอบรมเชิงลึกในหัวข้อ Deep Learning in Intelligent Video Analytics and Computer Vision Workshop

เรียนเชิญเข้าร่วมการอบรมเชิงลึกในหัวข้อ Deep Learning in Intelligent Video Analytics and Computer Vision Workshop

2-day Workshop in Chulalongkorn University (Faculty of Engineering) @ Bangkok Thailand.

Limited to only 30 seats!
Register by Aug 4, 2018 with registration fee $400 (save $50!)
Normal price: $450 after Aug 4 onwards

ลงทะเบียนได้ที่ >>http://bit.ly/2NF4xFn

DATE AND TIME
Thu, Aug 9, 2018, 9:00 AM – Fri, Aug 10, 2018, 5:00 PM (Indochina Time Thailand Time)

LOCATION
Faculty of Engineering, Chulalongkorn University

Khwaeng Pathum Wan, Krung Thep Maha Nakhon 10330

Important Reminder: Participants must bring their own laptop with Chrome browser installed and have experience in python. Please ensure that you meet the pre-requisites for both workshops.

iTrain Asia and Chula University partners with NVIDIA Deep Learning Institute (DLI) to offer hands-on training to developers, data scientists, and researchers looking to solve real world problems with deep learning across diverse industries such as self-driving cars, healthcare, online services and robotics.

This training is also supported by (i) TechData Thailand, (ii) CAT Telecom, and (iii) Department of Computer Engineering, Faculty of Engineering, Chulalongkorn University.

Important Reminder: Participants must bring their own laptop with Chrome browser installed and have experience in python. Please ensure that you meet the pre-requisites for both workshops.

DAY 1 – with Certificate (AUG 9)
HANDS-ON:
NVIDIA Deep Learning Institute Fundamentals Training
Pre-requisite: MUST have technical background and basic understanding of Deep Learning concepts Certificate: Participants will receive a DLI certificate for the workshop on the first day.

Course Outline:

Image Classification with DIGITS (120 min)

How to leverage deep neutral networks (DNN) within the deep learning workflow
Process of data preparation, model definition, model training and troubleshooting, validation testing and strategies for improving model performance using GPUs.
Train a DNN on your own image classification application
Object Detection with DIGITS (120 min)

Train and evaluate an image segmentation network
Neutral Network Deployment with DIGITS and TensorRT (120 min)

Uses a trained DNN to make predictions from new data
Show different approaches to deploying a trained DNN for inference
learn about the role of batch size in inference performance as well as virus optimisations that can be made in the inference process

DAY 2 (AUG 10)
LECTURES & HANDS-ON:
Intelligent Video Analytics with Deep Learning
Prerequisite: Python, Laptop with SSH (e.g., Windows with Putty or MobaXterm and Linux & Mac do not need any additional software.)

Course Outline:

Overview of Architectures for Computer Vision (90 min)
Lab 1: Deep learning with Keras (60 min)
Deployment with Deepstream and TensorRT (30 min)
Lab 2: Deployment for classification and detection tasks (30 min)
Transfer learning techniques (30 min)
Lab 3-1: Model adaptation (30 min)
Lab 3-2: Advanced techniques for adaptation (30 min)
Video action recognition (15 min)
Lab 4: Video action recognition (30 min)
Jetson Demo: deployment on Jetson (15 min)

ลงทะเบียนได้ที่ >>http://bit.ly/2NF4xFn

ABOUT YOUR TRAINERS:

DAY 1 Instructor:

DR. WARASINEE CHAISANGMONGKON, Ph.D.

Dr. Chaisangmongkon is a lecturer at the Institute of Field Robotics, King Mongkut’s University of Technology Thonburi and a research associate at Center of Neural Science at New York University. She was awarded a Ph.D. in Computational Neuroscience from Yale University, where she performed data analytics and used machine learning models to understand human brain. Upon joining KMUTT, she pursues research and technology development in the area of big data analytics, specialized in consumer behaviors and web mining.

In the last decade, Dr. Chaisangmongkon has been studying human cognition in the area of decision making and economic judgement. She used a multitude of data mining techniques to analyze big data in neuroscience and employed machine learning to make predictions about observable behaviors and associated neural mechanisms. She has extensive experiences building mathematical models of complex dynamical neural system on large-scale computing clusters. She collaborated with scientists from world-class research institutes including but not limited to University of Chicago, Johns Hopkins University, and IBM.

She also specializes in Large-scale machine learning for customer analytics, banking and financial services, retail, telecommunications, human resource analytics, predictive marketing, digital marketing.

DAY 2 Instructors:

PROF. EKAPOL CHUANGSUWANICH, Ph.D.

Ekapol Chuangsuwanich is a Faculty Member in the Department of Computer Engineering at Chulalongkorn University. He received the B.S. and S.M. degree in Electrical and Computer Engineering from Carnegie Mellon University in 2008 and 2009, respectively. He then joined the Spoken Language Systems Group at MIT Computer Science and Artificial Intelligence Laboratory. He received his Ph.D. degree in 2016 from MIT. His thesis work was on low-resource automatic speech recognition and representation learning using neural networks, which was part of the system that won Babel open keyword spotting challenge in 2016. With his expertise in multimedia retrieval, he is also one of the founding members of SmartVid.io, a startup working on organizing videos and images for the construction industry. In 2017, SmartVid.io was a runner-up in NVIDIA’s Inception competition for AI startups.

PROF. PEERAPON VATEEKUL, Ph.D.

Peerapon Vateekul received his Ph.D. degree from Department of Electrical and Computer Engineering, University of Miami (UM), Coral Gables, FL, U.S.A. in 2012. Currently, he is an assistant professor at Department of Computer Engineering, Faculty of Engineering, Chulalongkorn University, Thailand. Also, he is a deputy head of the department in academic affairs.

His research falls in the domain of machine learning, data mining, deep learning, text mining, and big data analytics. To be more specific, his works include variants of classification (hierarchical multi-label classification), data quality management, and applied deep learning techniques in various domains, such as, medicinal images and videos, satellite images, meteorological data, and text.

This workshop is brought to you by iTrain Asia, NVIDIA Deep Learning Institute, Chulalongkorn University, and CAT Telecommunications.

ลงทะเบียนได้ที่ >>http://bit.ly/2NF4xFn

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