ACML 2020: Workshop on Machine Learning in Thailand

Over the years, Machine Learning (ML) techniques have gained increasing attention from the large public. We believe that advances in ML will have a profound impact on our society: such impacts could be on productivity, employment, and competitiveness of companies or even nations. As ACML 2020 was planned to be held in Bangkok, Thailand, before going virtual, we would like to survey the state of ML applications and research in Thailand and neighbouring countries in South East Asia.

The workshop on Machine Learning in Thailand (MLIT) aims to bring together a diverse group of ML researchers, practitioners as well as researchers from other disciplines to present and discuss their projects with the other participants. Despite the online format, we hope that the workshop would help establish and stimulate ML research activities in Thailand and in the region.

List of talks:
0:00 Opening
14:33 Kwanchiva Thangthai, Virtual assistant and avatar: The first step
39:33 Natthaphon Hongcharoen, Transferable Reinforcement Learning for Board Games
50:57 Korakot Chaovavanich, Improving Google Colaboratory to serve Thailand Machine Learning Community
xx:xx (no recording) Konpat Preechakul, High resolution weakly supervised localization architectures for medical images
01:06:00 Thiparat Chotibut, Demystifying Machine Learning Algorithms with Methods of Theoretical Physics
01:18:20 Break
01:24:00 Sorn Sooksatra, Redesigned Skip-Network for Crowd Counting with Dilated Convolution and Backward Connection
01:36:15 Kanchit Rongchai, Rapid Prototyping of an Inexpensive Camera with Low-Code Machine Learning Wildlife Recognition for Pangolin Conservation Research in Thailand
01:51:00 Chompakorn Chaksangchaichot, A Large-Scale Data Collection from Internet for Thai Language and Speech Processing
02:01:00 Charin Polpanumas, Thai-to-Any-Language Parallel Corpora from Wikipedia Dumps with CRF-based Sentence Segmentation and Multilingual Sentence Encoder
02:15:00 Witchapong Daroontham, End-to-end ML Pipelines in Big Retail: Showcases of Recommendation & Search Systems at TOPS Online