Parallel learning: Overview and perspective for computational learning across Syn2Real and Sim2Real
Q Miao, Y Lv, M Huang, X Wang… - IEEE/CAA Journal of …, 2023 - ieeexplore.ieee.org
The virtual-to-real paradigm, ie, training models on virtual data and then applying them to
solve real-world problems, has attracted more and more attention from various domains by …
solve real-world problems, has attracted more and more attention from various domains by …
A survey on deep domain adaptation for lidar perception
Scalable systems for automated driving have to reliably cope with an open-world setting.
This means, the perception systems are exposed to drastic domain shifts, like changes in …
This means, the perception systems are exposed to drastic domain shifts, like changes in …
At the Dawn of Generative AI Era: A tutorial-cum-survey on new frontiers in 6G wireless intelligence
As we transition from the 5G epoch, a new horizon beckons with the advent of 6G, seeking a
profound fusion with novel communication paradigms and emerging technological trends …
profound fusion with novel communication paradigms and emerging technological trends …
Parallel radars: from digital twins to digital intelligence for smart radar systems
Radar is widely employed in many applications, especially in autonomous driving. At
present, radars are only designed as simple data collectors, and they are unable to meet …
present, radars are only designed as simple data collectors, and they are unable to meet …
Gan-based lidar translation between sunny and adverse weather for autonomous driving and driving simulation
J Lee, D Shiotsuka, T Nishimori, K Nakao, S Kamijo - Sensors, 2022 - mdpi.com
Autonomous driving requires robust and highly accurate perception technologies. Various
deep learning algorithms based on only image processing satisfy this requirement, but few …
deep learning algorithms based on only image processing satisfy this requirement, but few …