Ujjwal Saxena

Automold--Road-Augmentation-Library. This library augments road images to introduce various real world scenarios that pose challenges for training neural networks of Autonomous vehicles. Automold is created to train CNNs in specific weather and road conditions.

CarND-Advanced-Lane-Lines-Detection-T1P4. This is the advanced lane detection project which includes advanced image processing to detect lanes irrespective of the road texture, brightness, contrast etc. I used Image warping and sliding window approach to find and plot the lanes. This makes it better with the lane curves.

road-glare-removal-tests. Jupyter Notebook

Semantic-Segmentation-T3P2. Semantic segmentation uses transposed convolutions in the decoder part to segment the images in classes. This projects implements a FCN8 architecture to detect the roads in the image.

Path-Planning-Project-T3P1. Prediction, behaviour planning and trajectory