Name: Tai Do
Type: User
Company: Pattern Recognition Lab
Bio: PostDoc at Pattern Recognition Lab
Department of Artificial Intelligent Convergence, Chonnam National University, Gwangju, Korea
Location: Chonnam National University, Gwangju, Korea
Blog: http://dntai.github.io
Tai Do's Projects
Train and Deploy Machine Learning Model With Web Interface - Docker, PyTorch & Flask
2014 NTU BIME Machine learning course final project.
Python code for Machine Learning course from Coursera
This is the offline fitting portion of my paper: "Real-Time Continuous Pose Recovery of Human Hands Using Convolutional Networks"
Source code to our paper: "Learning a Variational Network for Reconstruction of Accelerated MRI Data"
mtcnn in python
Source code for conference paper at SoICT'16
Hungarian algorithm + Kalman filter multitarget tracker implementation.
Accompany code to reproduce the baselines of the International Multimodal Sentiment Analysis Challenge (MuSe 2020).
MuSE Trust 2020
An interactive book on deep learning. Much easy, so MXNet. Wow.
Winning models for the N+1 Fish, N+2 Fish competition.
NumPy-compatible multidimensional arrays in C++
A Developer Roadmap to becoming a Node.js developer in 2019
Non-local U-Nets for Biomedical Image Segmentation
Team notebook for the ACM-ICPC World Finals 2018.
IPython Notebook experiments
Neural network library in Python
Object Detection Framework using HOG as descriptor and Linear SVM as classifier.
Object perception tasks: detection, tracking and classification.
This repository contains code corresponding to the paper Learning to Reconstruct People in Clothing from a Single RGB Camera.
Source code for the book OpenCV3 Computer Vision Application Programming Cookbook 2016
http://www.youtube.com/watch?v=bUrjFGMfwas
OPENCV: QR CODE DETECTION AND EXTRACTION
Hand Tracking And Gesture Detection (OpenCV)
An open source implementation of DTAM
OpenFace ā a state-of-the art tool intended for facial landmark detection, head pose estimation, facial action unit recognition, and eye-gaze estimation.