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Muhammad Nassef's Projects

behavioral-cloning-project icon behavioral-cloning-project

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.

extended-kalman-filter-project icon extended-kalman-filter-project

Implementation of Extended Kalman Filter algorithm in C++ capable of performing the fusion of Lidar and Radar sensors data for tracking a pedestrian's motion in two dimensions.

lane-lines-detection icon lane-lines-detection

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.

traffic-signs-classifier icon traffic-signs-classifier

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.

unscented-kalman-filter-project icon unscented-kalman-filter-project

Implementation an Unscented Kalman Filter algorithm in C++ capable of accurately performing the fusion of Lidar and Radar sensors data for tracking a turning object using Constant Speed Constant Turn Rate (CTRV) Motion model.

vehicle-detection-and-tracking icon vehicle-detection-and-tracking

Created a vehicle detection and tracking pipeline with OpenCV, histogram of oriented gradients (HOG), and support vector machines (SVM). Optimized and evaluated the model on video data from a automotive camera taken during highway driving.

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