Company News
Panasonic R&D Center Singapore Takes Second Place at the Second Edition of the AI Driving Olympics
May 2019 | Project
Panasonic R&D Center Singapore finished second among the top 5 teams that made the cut from among the 50 teams in a leading international competition – that is, the second edition of the AI Driving Olympics, where Panasonic R&D Center Singapore is last year’s champion. (Reference: https://www.duckietown.org/archives/37690)
Termed “MYF” (username), Panasonic R&D Center Singapore emerged as one of the top 2 finalists and then moved forward to the more complicated challenges of Lane Following with Vehicles and Lane Following with Vehicles and Intersections. The other finalist (termed “JBRRussia”) was eventually crowned the winner of this edition.
The competition was held in conjunction with the premier International Conference on Robotics and Automation (ICRA) 2019.
Related Posts
Acceptance of two papers by ICCV’17 Workshop on MS-Celeb-1M: Recognizing One Million Celebrities in the Real World
Panasonic R&D Center Singapore, collaborating with the National University of Singapore (NUS), co-authored two papers that have been accepted by ICCV (International Conference on Computer Vision*) 2017 Workshop on MS-Celeb-1M: Recognizing One Million Celebrities in the Real World, which will be held in Venice, Italy, on October 28th, 2017.
Read morePanasonic introduces more of the 2021 OLED and LED TV line-up powered by Panasonic R&D Center Singapore’s AI engine
Following the debut of its flagship JZ2000 OLED TV at CES 2021, Panasonic unveiled more of its OLED and LED…
Read morePanasonic R&D Center Singapore’s Paper Accepted for Publication in an Upcoming Issue of the IEEE Transactions on Intelligent Vehicles (T-IV)
Teaming up with Nanjing University of Science and Technology (NUST), Panasonic R&D Center Singapore co-authored a journal paper titled “Vehicle…
Read morePanasonic R&D Center Singapore Achieves No. 1 Accuracy of Face Recognition on the IJB-C Dataset
Panasonic R&D Center Singapore achieved the Best Accuracy of Face Recognition on the IJB-C dataset under three different protocols, namely 1:1 mixed verification, 1:N mixed identification and 1:1 covariate verification.
Read more
