This Project is Semantic Segmentation Project of Term 3 of Udacity Self-Driving Car Engineer Nanodegree.
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Updated
Sep 6, 2017 - Python
This Project is Semantic Segmentation Project of Term 3 of Udacity Self-Driving Car Engineer Nanodegree.
This code segments out the drive-able portion of the road from the surrounding.
This is a project to detect road signs using the Viola and jones Algorithm.
This repository contains codes and DL model for improving and analysing Indian transport infrastructure
Road detection in satellite imagery using fully convolutional neural networks.
Semantically segment the road in the given image.
Simple road detection with Python and OpenCV
SNE-RoadSeg for Freespace Detection in PyTorch, ECCV 2020
Implementation of the paper "ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data" in TensorFlow.
Semantic Segmentation with U-net and MobileUNETV2.
Neural network to predict and draw traffic lanes.
A practical implementation of pixel level segmentation based road detection and steering angle estimation methods.
Path/Road Following Differential Vehicle Bot.
Ultra Fast Structure-aware Deep Lane Detection (ECCV 2020)
ENPM673: Project 2 Problem 2 and 3. In this project I detect the road lanes by performing image transformations on each frame of continuous input, further developing the program to also visually predict upcoming turns
A Pytorch implementation of DeepCrack and RoadNet projects.
Road Lane Dection using OpenCV in python
Autonomous Formula 1 by camera
Implementation of paper "Random-Walker Monocular Road Detection in Adverse Conditions Using Automated Spatiotemporal Seed Selection"
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