Results 221 to 230 of about 65,126 (264)

Visual routines for autonomous driving

Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271), 2002
The paper describes visual routines based on models of color and shape, as well as crucial issues involving the scheduling of such routines. The visual routines are developed in a unique platform. The view from a car driving in a simulated world is feed into a Datacube pipeline video processor. The use of this simulation provides a flexible environment
Garbis Salgian, Dana H. Ballard
openaire   +1 more source

Deep Learning for Autonomous Driving

2019 Digital Image Computing: Techniques and Applications (DICTA), 2019
In this paper we look at Deep Learning methods using TensorFlow for autonomous driving tasks. Using scale model vehicles in a traffic scenario similar to the Audi Autonomous Driving Cup and the Carolo Cup, we successfully used Deep Learning stacks for the two independent tasks of lane keeping and traffic sign recognition.
Nicholas Burleigh, Jordan King, Thomas Bräunl   +2 more
openaire   +1 more source

Autonomous Driving Car Competition

2019
This paper presents the construction of an autonomous robot to participating in the autonomous driving competition of the National Festival of Robotics in Portugal, which relies on an open platform requiring basic knowledge of robotics, like mechanics, control, computer vision and energy management.
João Pedro Alves, Nuno M. Fonseca Ferreira, António Valente, Salviano Soares, Vítor Filipe   +4 more
openaire   +1 more source

Autonomous driving

it - Information Technology, 2015
Johann Marius Zöllner, Thomas Schamm
openaire   +3 more sources

Technological Challenges in Autonomous Driving

Proceedings of the 1st International Workshop on Communication and Computing in Connected Vehicles and Platooning, 2018
Automotive world is quickly moving towards another revolution of driverless cars. To realize this dream in large scale will see lots of challenges in terms of product development. In this talk, I would like to address different problems which automotive industry will have to face to make this a reality.
A. K. Prakash, Hrishikesh Venkataraman
openaire   +1 more source

The ApolloScape Dataset for Autonomous Driving

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2018
Scene parsing aims to assign a class (semantic) label for each pixel in an image. It is a comprehensive analysis of an image. Given the rise of autonomous driving, pixel-accurate environmental perception is expected to be a key enabling technical piece.
Xinyu Huang 0001, Xinjing Cheng, Qichuan Geng, Binbin Cao, Dingfu Zhou, Peng Wang 0001, Yuanqing Lin, Ruigang Yang   +7 more
openaire   +2 more sources

Towards Autonomous Driving

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023
openaire   +1 more source

AUTONOMOUS DRIVING SYSTEM

2022
SONE ATSUSHI, KUNIHIRO YOJI, YOKOTA TAKAHIRO, IRIE RYO, WATANABE YOSHINORI, AMANO MASATERU   +5 more
openaire   +10 more sources

Lane Finding for Autonomous Driving

2019
The problem of lane finding is one of the main components of scene understanding for autonomous driving. This paper presents the application of computer vision to lane finding on motorways. This technique is used to transform an image captured by a camera into binary form and apply a moving histogram window to derive the most likely position of the ...
openaire   +1 more source

A review of high-definition map creation methods for autonomous driving

Engineering Applications of Artificial Intelligence, 2023
Xianke Lin, Haoxiang Lang, Sabir Hossain   +2 more
exaly