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Sanghoon Yoo's Projects

advanced-lane-findings icon advanced-lane-findings

The goal of this project is to create software pipeline to identify lane boundaries from a video using OpenCV.

behavioral-cloning-with-deep-learning icon behavioral-cloning-with-deep-learning

Leveraged deep neural networks and convolutional neural networks to clone driving behavior using Keras. Trained, validated and tested a model to output a steering angle to an autonomous vehicle. Data collection was done within a simulator environment. Used image data and steering angles to train a neural network and then used this model to drive the car autonomously around the track in a simulator.

elevator-simulator icon elevator-simulator

Simulates four elevators available to take passengers up and down a 100 floor building

extended-kalman-filter icon extended-kalman-filter

Applied a extended Kalman filter in C++ with provided simulated lidar and rader measurements detecting bicycle that travels around the vehicle. Kalman filter tracks the bicycle's position and velocity from estimating the state of a moving object of interest with noisy lidar and radar measurements.

ml-web-app icon ml-web-app

Train and Deploy Simple Machine Learning Model With Web Interface - Docker, PyTorch & Flask

traffic-sign-classifier icon traffic-sign-classifier

Utilized deep neural networks and convolutional neural networks to classify traffic signs using TensorFlow. Trained and validated a model so it can classify traffic sign images using the German Traffic Sign Dataset. After the model is trained, tried out my model on images of German traffic signs that I found on the web, which was new test set.

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