default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDAutonomous Vehicles and Machines 2019: Burlingame, CA, USA
- Patrick Denny, Robin B. Jenkin, Buyue Zhang:
Autonomous Vehicles and Machines 2019, Burlingame, CA, USA, January 13-17, 2019. Society for Imaging Science and Technology 2019
Articles
- Conference Overview and Papers Program. 1-8
- Paul J. Kane:
Signal detection theory and automotive imaging. 1-8 - Uwe Artmann, Marc Geese, Max Gäde:
Contrast detection probability - Implementation and use cases. 1-13 - Christian Winkens, Veronika Adams, Dietrich Paulus:
Automatic shadow detection using hyperspectral data for terrain classification. 1-6 - Christian Fuchs, Dietrich Paulus:
Integration of advanced stereo obstacle detection with perspectively correct surround views. 1-10 - Raghav Nagpal, Chaitanya Krishna Paturu, Vijaya Ragavan, Navinprashath R. R., Radhesh Bhat, Dipanjan Ghosh:
Real-time traffic sign recognition using deep network for embedded platforms. 1-8 - Willem P. Sanberg, Gijs Dubbelman, Peter H. N. de With:
From stixels to asteroids: Towards a collision warning system using stereo vision. 1-7 - Eren Unlu, Emmanuel Zenou, Nicolas Rivière, Paul-Edouard Dupouy:
An autonomous drone surveillance and tracking architecture. 1-7 - Hiroyuki Fujimoto, Junya Morimoto, Takuya Hayashi, Junji Yamato
, Hiroyuki Ishii, Jun Ohya, Atsuo Takanishi:
Pattern and frontier-based, efficient and effective exploration of autonomous mobile robots in unknown environments. 1-7 - Zachariah Carmichael, Benjamin Glasstone, Frank Cwitkowitz, Kenneth Alexopoulos, Robert Relyea, Raymond W. Ptucha:
Autonomous navigation using localization priors, sensor fusion, and terrain classification. 1-7 - Kurt Pichler, Sandra Haindl, Daniel Reischl, Martin Trinkl:
Autonomous highway pilot using Bayesian networks and hidden Markov models. 1-7 - Ciarán Hughes, Sunil Chandra, Ganesh Sistu, Jonathan Horgan, Brian M. Deegan, Sumanth Chennupati, Senthil Kumar Yogamani:
DriveSpace: Towards context-aware drivable area detection. 1-9 - Peter van Beek:
Image-based compression of LiDAR sensor data. 1-7 - Lucie Yahiaoui, Ciarán Hughes, Jonathan Horgan, Brian M. Deegan, Patrick Denny, Senthil Kumar Yogamani:
Optimization of ISP parameters for object detection algorithms. 1-8 - Navinprashath R. R., Radhesh Bhat:
Learning based demosaicing and color correction for RGB-IR patterned image sensors. 1-6 - Orit Skorka, Paul J. Kane, Radu Ispasoiu:
Color correction for RGB sensors with dual-band filters for in-cabin imaging applications. 1-8 - Michal Uricár, Pavel Krízek, David Hurych, Ibrahim Sobh, Senthil Kumar Yogamani, Patrick Denny:
Yes, we GAN: Applying adversarial techniques for autonomous driving. 1-17 - Christian Winkens, Florian Sattler, Dietrich Paulus:
Deep dimension reduction for spatial-spectral road scene classification. 1-9 - Zhenyi Liu, Minghao Shen, Jiaqi Zhang, Shuangting Liu, Henryk Blasinski, Trisha Lian, Brian A. Wandell:
A system for generating complex physically accurate sensor images for automotive applications. 1-6 - Mónica López-González:
Today is to see and know: An argument and proposal for integrating human cognitive intelligence into autonomous vehicle perception. 1-9 - Dongwoo Kang, Jingu Heo, Byongmin Kang, Dongkyung Nam:
Pupil detection and tracking for AR 3D under various circumstances. 1-5 - Ying-Wei Chuang, Chien-Hao Kuo, Shih-Wei Sun, Pao-Chi Chang:
Driver behavior recognition using recurrent neural network in multiple depth cameras environment. 1-7
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2025-12-01 23:08 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
