side-projects/ (4 entries)
[2025] Yuzu Money Backend Developer Neobank and yield platform - earn interest on savings with competitive rates and seamless money management↗ [2024] Nova Service Loyalty App Backend Developer Loyalty rewards app for Nova Service customers - earn points, redeem rewards, and track membership benefits↗ [2021] Pokerage Backend Developer Online poker platform with real-time multiplayer gameplay, tournaments, and AI bots for practice matches↗ [2019] VSmart FaceID Parttime Help optimizing the NCNN model size for mobile application↗open-source/ (9 entries)
[2022] Go Socket.io Owner Upgrade the library to work with newest socket.io version (v4)↗ [2021] Google Cloud SDK PubSub Emulator Owner Google Cloud SDK PubSub Emulator for local development↗ [2021] X-Crafter Owner a go template breaker and builder helps you easily building a SDK↗ [2021] LogrGorm2 Owner a logr logging driver for gorm v2↗ [2021] Gomw Owner A framework for fasten creating Go HTTP Middleware↗ [2021] Go bootstraper Owner A bootstraper that help you create a standardized go project at lightning speed↗ [2020] JsonCase Owner a go package for converting json case to various cases↗ [2019] Helm Charts (Telegraf) Contributor Template update and bugs fixed for Influx Telegraf chart.↗ [2019] Elasticsearch Vietnamese Analysis Developer An Open Source Vietnamese ElasticSearch Analyzer for Everyone.↗publications/ (3 entries)
[2019] The New High-Performance Face Tracking System based on Detection-Tracking and Tracklet-Tracklet Association in Semi-Online Mode Co-Author Despite recent advances in multiple object tracking and pedestrian tracking, multiple-face tracking remains a challenging problem. In this work, the authors propose a framework to solve the problem in semi-online manner (the framework runs in real-time speed with two-second delay).↗ [2018] Python programming self-study Co-Author A book for python basic learner. My laboratory and I co-authored this book to help students learn python programming.↗ [2017] Video segmentation using keywords Co-Author At DAVIS-2016 Challenge, many state-of-art video segmentation methods achieve potential results, but they still much depend on annotated frames to distinguish between background and foreground. It takes a lot of time and efforts to create these frames exactly. In this paper, we introduce a method to segment objects from video based on keywords given by user.↗Check out my GitHub for more projects and open source contributions.