KYUNG MO KWEON

Table of Contents

1 Machine Learning

1.1 American Sign Language Recognition with HMM

1.1.1 Overview

  • Convert Sign Langauge to English words
  • Achieved the WER(Word Error Rate) of 43.8%
  • Used Plain Hidden Markov Models and Ensembles

1.1.2 Link

1.2 Reinforcement Learning

1.2.1 Overview

1.3 Spending Visualization

1.3.1 Overview

  • Used random forest to categorize my monthly expenditures
  • Visualized monthly spending in comparison to the previous month

1.3.2 Link

2 Self Driving Car

2.1 Vehicle Detection

2.1.1 Overview

  • Segmented vehicles on a picture or a video frame with the IOU (Intersection of Union) of ~80%
  • Implemented the Convolutional Networks for Image Segmentation (U-Net) from scratch

2.1.2 Link

2.2 Path Planning

2.2.1 Overview

  • Generates a path plan that can drive on the highway
  • Implemented an efficient(lane change if necessary) and safe trajectory

2.2.2 Link

2.3 Vehicle Control with a Model Predictive Controller

2.3.1 Overview

  • Successfully drove vehicles autonomously, maintaining high-speed of over 70+ mph
  • Implemented a model predictive controller in the simulator
  • Used C++ and WebSocket to communicate with the simulator

2.3.2 Link

2.4 Vehicle Localization using Unscented Kalman Filter

2.4.1 Overview

  • Localized the vehicle in the simulator with the root mean squared error (RMSE) of ~0.1
  • Implemented Unscented Kalman Filter in C++
  • Used googletest to follow the Test Driven Development (TDD)

2.4.2 Link

2.5 Traffic Sign Recognition

2.5.1 Overview

  • Used the multiple layers of Convolution Neural Network(CNN) in Keras
  • Used image augmentation tricks such as color shift, rotation, and zooming.
  • Achieved 98.01% accuracy on the test data

2.5.2 Link

2.6 Finding Driving Lanes

2.6.1 Overview

  • Used OpenCV to detect driving lanes on the road
  • Used canny edge detection and color thresholding
  • Written in Python

2.6.2 Link

  • Jupyter Notebook: link

3 Web

3.1 Landing Page

Mountain Landing

3.1.1 Overview

  • Use Webpack, Pug, Sass

3.1.2 Link

3.2 Mango Commerce

3.2.1 Overview

  • Fruits/Vegetable Marketplace Demo
  • Admin users can create an order using a custom chatbot
  • Used Elixir, Phoenix, Bootstrap, WebSocket, ES6

3.2.2 Link

3.3 PR-12

3.3.1 Overview

PR-12 is the reading/study group organized in Tensorflow KR Facebook Group. The objective is to read/discuss deep learning papers every week hosted in Awesome Deep Learning Papers.

3.3.2 Link

3.4 Hue Control Dashboard

3.4.1 Overview

  • Control smart home plugs such as Phillips Hue and TP Link smart plugs
  • Used Ajax, Webpack, Elm, ES6, CSS

3.4.2 Link

3.5 Nato Phonetic Convert

3.5.1 Overview

  • Convert English Sentence to Nato Phonetic Words

For example,

M   ⟼   Mike
O   ⟼   Oscar

K   ⟼   Kilo
W   ⟼   Whiskey
E   ⟼   Echo
O   ⟼   Oscar
N   ⟼   November
  • Used Elm, CSS

3.5.2 Link

3.6 Kaggle Clone

3.6.1 Overview

  • Kaggle is a competition website for data scientist
  • This is a clone version of Kaggle using Django, Postgres

3.6.2 Link

3.7 Price Alert

3.7.1 Overview

  • Users can set up a price alert with the target price
  • Users will get an alert if the price goes down to the target price
  • Flask and MongoDB were used

3.7.2 Link

3.8 Question Asking Platform for Conference/Seminar

3.8.1 Overview

  • Users can write/upvote/downvote a question
  • Sync real-time using websockets
  • Written in Elm

3.8.2 Link

3.9 Simple Weather Ajax in Angular.js (v1)

3.9.1 Overview

  • Used the openweathermap.org API service to query a weather of a city
  • Angular.js(v1)

3.9.2 Link

3.10 Blog REST API

3.10.1 Overview

  • Implemented RESTful Blog service through Django Rest Framework

3.10.2 Link

4 Android/iOS

4.1 Employee Manager App

Demo Image

4.2 Overview

As a manager, I want to

  • add an employee
  • delete an employee
  • text an employee the work shift
  • edit the employee information

4.3 Link

5 Utils

5.1 sh2md

5.1.1 Overview

Record your shell session and produce in the markdown format

5.1.2 Link

5.2 Shell in Scala

5.2.1 Overview

Shell Implementation in Scala

5.2.2 Link

5.3 CSS Autoprefix Plugin for Emacs

5.3.1 Overview

Turn this code

  div {
    display: flex;
  }

into

  div {
    display: -webkit-box;
    display: -ms-flexbox;
    display: flex;
  }

5.3.2 Link

5.4 gbrowse

5.4.1 Overview

Open any git repository file in the browser in GitHub Respository

gbrowse # open current branch in GitHub (e.g., https://github.com/kkweon/gbrowse/tree/master)
gbrowse src/index.ts # (e.g., https://github.com/kkweon/gbrowse/tree/master/src/index.ts)

5.4.2 Link

5.5 Trello2Text

5.5.1 Overview

Export trello cards to text with Slack markdown format

5.5.2 Link

5.6 CalTrain Shuttle Bus Alexa Skill

5.6.1 Overview

  • There is a shuttle bus from Broadway CalTrain Station to Millbrae CalTrain Station
  • Created a simple Alexa skill that users can ask Alexa to get the shuttle bus schedule
  • Used Node.js, AWS Serverless Lambda, Mocha, TDD

5.6.2 Link

5.7 Keras Docset for Dash/Zeal

5.7.1 Overview

  • Allows users to lookup Keras API easily
  • Created a Keras docset for Zeal/Dash

5.7.2 Link

5.8 Identicon Generator

5.8.1 Overview

  • Identicon refers to an image that is unique and can represent one’s identity (Like UUID but in image format)
  • Used Elixir and Erlang library

5.8.2 Link

5.9 Reddit Crawler in Haskell

5.9.1 Overview

  • Valuable machine learning related information are posted in /r/MachineLearning every day
  • Instead of visiting the website and risking my time (since it’s very addictive), I wrote a crawler that crawls the top 20 posts and sends me an email
  • Used Haskell, Stack, Docker

5.9.2 Link

5.10 DeepLearningZeroToAll/ReinforcementZeroToAll

5.10.1 Overview

  • Created to teach people deep learning and reinforcement learning in Tensorflow
  • Maintainer for both repositories