Won 28th place in this competition to accurately detect cars and road in images from CARLA simulator at 10 frames per second.
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Updated
Dec 7, 2022 - Python
Won 28th place in this competition to accurately detect cars and road in images from CARLA simulator at 10 frames per second.
MASK-RCNN implementation for Lyft Perception Challenge
Semantic segmentation models for self-driving cars. Models developed for "Lyft Udacity Challenge for Self-driving Cars".
Road Image Segmentation for Autonomous Vehicle using Fully Convolution Network (FCN).
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