Segmentation and Depth Estimation of Urban Road Using Monocular Camera and Convolutional Neural Networks

Segmentation and Depth Estimation of Urban Road Using Monocular Camera and Convolutional Neural Networks

Deep learning for safe autonomous transport is rapidly emerging. Fast and robust perception for autonomous vehicles will be crucial for future navigation in urban areas with high traffic and human interplay. Previous work focuses on extracting full image depth maps, or finding specific road features...

Full description

Bibliographic Details
Main Author: Djikic, Addi
Format: Others
Language:English
Published: KTH, Robotik, perception och lärande, RPL 2018
Subjects:
AI
ANN
CNN
semantic
segmentation
autonomous
Scania
driving
road
pixel
classification
regression
real time
monocular
depth
estimation
convolutional
neural
networks
deep
learning
perception
camera
vehicles
supervised
tensorflow
Cityscapes
machine learning
autoencoder
decoder
encoder
Computer Vision and Robotics (Autonomous Systems)
Datorseende och robotik (autonoma system)
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-235496

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-235496

Similar Items