This repository contains the source code and write-ups of all the projects I've done in the Udacity Self-Driving Car Engineer Nanodegree.
Enjoy! :-)
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Detected highway lane lines on a video stream. Used OpencV image analysis techniques to identify lines, including Hough Transforms and Canny edge detection. |
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Built and trained a deep neural network to classify traffic signs, using TensorFlow. Experimented with different network architectures. Performed image pre-processing and validation to guard against overfitting. |
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A car drives in a simulated environment by cloning the behavior seen during training mode. Leveraging TensorFlow and Keras, a deep learning network predicts the proper steering angle given training examples. |
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Built an advanced lane-finding algorithm using distortion correction, image rectification, color transforms, and gradient thresholding. Identified lane curvature and vehicle displacement. Overcame environmental challenges such as shadows and pavement changes. |
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Created a vehicle detection and tracking pipeline with OpenCV, histogram of oriented gradients (HOG), and support vector machines (SVM). Implemented the same pipeline using a deep network to perform detection. Optimized and evaluated the model on video data from a automotive camera taken during highway driving |
