Vehicle Detection and Tracking
Advanced Lane Finding
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.
Created a vehicle detection and tracking pipeline with OpenCV, a histogram of oriented gradients (HOG), and support vector machines (SVM). Optimized and evaluated the model on video data from an automotive camera taken during highway driving.
Traffic Sign Classification
Built and trained a convolutional neural network for end-to-end driving in a simulator, using TensorFlow and Keras. Used optimization techniques such as regularization and dropout to generalize the network for driving on multiple tracks.
Use Deep Learning to Clone Driving Behavior
Skills: Python, TensorFlow, Keras, Computer Vision, Machine Learning, Deep Learning
Apart from the projects mentioned above, I have taken multiple Online Classes offered by EdX, Coursera and Udacity, projects of which working on problems dealing with object recognition and detection, Transfer Learning, Natural Language Processing (NLP) etc. Please feel free to check my Github profile to read more details about these projects.
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