silverwhere
Mechanical Engineer with 17 years + automotive experience. Found a new love with computer vision, deep-learning for self-driving vehicles.
National DefenceOttawa, Ontario
Pinned Repositories
Advanced-Lane-Finding
Advanced computer vision techniques to identify lanes, the position of the vehicle within the lane, the radius of curvature of the lane.
Behavioural-Cloning
I utilized end-to-end deep learning using convolutional neural networks (CNNs) to map the raw pixels from (3) front-facing cameras to the steering commands for a self-driving car.
CarND-Object-Detection-Lab
Extended-Kalman-Filter
Utilized an Extended Kalman Filter and Sensor Fusion to estimate the state of a moving object of interest with noisy lidar and radar measurements. The project involved utilzing lidar data (Point Cloud) for position and radar data (Doppler) for radial velocity.
Finding-Lane-Lines
Highway-Driving-Path-Planning
Create a path planner that is able to navigate a car safely around a virtual highway
Intro-to-Self-Driving-Cars---Udacity
Class projects for the Udacity Intro to Self Driving Vehicles nanodegree - In this program, I applied Python skills, and C++, apply matrices and calculus in code, computer vision and machine learning. These concepts will be applied to solving self-driving car problems.
Kidnapped-Vehicle---Particle-Filter
Utilizing data from initial GPS estimates and LIDAR data, I can use a particle filter based on the vehicle's reported observations of objects nearby to localize it and find it!
Self-Driving-Car-Nanodegree---Udacity
Self Driving Car Nanodegree Offered By Udacity
Traffic-Sign-Classifier
I utilized deep neural networks and convolutional neural networks to classify traffic signs. I trained and validated a model so it can classify traffic sign images using the German Traffic Sign Dataset.
silverwhere's Repositories
silverwhere/Self-Driving-Car-Nanodegree---Udacity
Self Driving Car Nanodegree Offered By Udacity
silverwhere/Extended-Kalman-Filter
Utilized an Extended Kalman Filter and Sensor Fusion to estimate the state of a moving object of interest with noisy lidar and radar measurements. The project involved utilzing lidar data (Point Cloud) for position and radar data (Doppler) for radial velocity.
silverwhere/Advanced-Lane-Finding
Advanced computer vision techniques to identify lanes, the position of the vehicle within the lane, the radius of curvature of the lane.
silverwhere/Highway-Driving-Path-Planning
Create a path planner that is able to navigate a car safely around a virtual highway
silverwhere/Traffic-Sign-Classifier
I utilized deep neural networks and convolutional neural networks to classify traffic signs. I trained and validated a model so it can classify traffic sign images using the German Traffic Sign Dataset.
silverwhere/Behavioural-Cloning
I utilized end-to-end deep learning using convolutional neural networks (CNNs) to map the raw pixels from (3) front-facing cameras to the steering commands for a self-driving car.
silverwhere/Finding-Lane-Lines
silverwhere/Kidnapped-Vehicle---Particle-Filter
Utilizing data from initial GPS estimates and LIDAR data, I can use a particle filter based on the vehicle's reported observations of objects nearby to localize it and find it!
silverwhere/CarND-Object-Detection-Lab
silverwhere/Intro-to-Self-Driving-Cars---Udacity
Class projects for the Udacity Intro to Self Driving Vehicles nanodegree - In this program, I applied Python skills, and C++, apply matrices and calculus in code, computer vision and machine learning. These concepts will be applied to solving self-driving car problems.
silverwhere/Mask_RCNN
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
silverwhere/Sensor-Fusion
Sensor Fusion for 3D Object Detection for Driverless Cars
silverwhere/silverwhere
Config files for my GitHub profile.
silverwhere/System-Integration---Capstone-Project
Self Driving Car Engineer Capstone Project
silverwhere/Traffic-Light-Classification
A detailed tutorial on how to build a traffic light classifier with TensorFlow for the capstone project of Udacity's Self-Driving Car Engineer Nanodegree Program.