Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Zuxin Liu"'
Autor:
Hasan Asy'ari Arief, Mansur Arief, Guilin Zhang, Zuxin Liu, Manoj Bhat, Ulf Geir Indahl, Havard Tveite, Ding Zhao
Publikováno v:
IEEE Access, Vol 8, Pp 131848-131858 (2020)
Addressing the need for high-quality, time efficient, and easy to use annotation tools, we propose SAnE, a semiautomatic annotation tool for labeling point cloud data. The contributions of this paper are threefold: (1) we propose a denoising pointwis
Externí odkaz:
https://doaj.org/article/6e505b86e7b14d1bb51fa39eb2b7f3bf
Publikováno v:
Biotechnology for Biofuels, Vol 11, Iss 1, Pp 1-16 (2018)
Abstract Background High-throughput evaluation of lignocellulosic biomass feedstock quality is the key to the successful commercialization of bioethanol production. Currently, wet chemical methods for the determination of chemical composition and bio
Externí odkaz:
https://doaj.org/article/92916366b4c349cf99da24a76e2ef78d
Publikováno v:
Italian Journal of Agronomy, Vol 13, Iss 3 (2018)
Jerusalem artichoke (Helianthus tuberosus L.) has been recognized as being a biomass crop for energy and livestock forage production. In this study, 26 Jerusalem artichoke clones previously collected from 24 provinces of China were grown under semiar
Externí odkaz:
https://doaj.org/article/b0e7c78f76ae4397b8bf42118227f42e
Publikováno v:
2022 2nd International Conference on Big Data, Artificial Intelligence and Risk Management (ICBAR).
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
The past few years have witnessed an increasing interest in improving the perception performance of LiDARs on autonomous vehicles. While most of the existing works focus on developing new deep learning algorithms or model architectures, we study the
Autor:
Guilin Zhang, Mansur Arief, Ding Zhao, Manoj Bhat, Håvard Tveite, Zuxin Liu, Ulf Geir Indahl, Hasan Asyari Arief
Publikováno v:
IEEE Access, Vol 8, Pp 131848-131858 (2020)
131848-131858
IEEE Access
131848-131858
IEEE Access
Addressing the need for high-quality, time efficient, and easy to use annotation tools, we propose SAnE, a semiautomatic annotation tool for labeling point cloud data. The contributions of this paper are threefold: (1) we propose a denoising pointwis
Publikováno v:
ICRA
Safety is a critical concern when deploying reinforcement learning agents for realistic tasks. Recently, safe reinforcement learning algorithms have been developed to optimize the agent’s performance while avoiding violations of safety constraints.
Publikováno v:
Biotechnology for Biofuels, Vol 11, Iss 1, Pp 1-16 (2018)
Biotechnology for Biofuels
Biotechnology for Biofuels
Background High-throughput evaluation of lignocellulosic biomass feedstock quality is the key to the successful commercialization of bioethanol production. Currently, wet chemical methods for the determination of chemical composition and biomass dige
Publikováno v:
IROS
Multi-agent navigation in dynamic environments is of great industrial value when deploying a large scale fleet of robot to real-world applications. This paper proposes a decentralized partially observable multi-agent path planning with evolutionary r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ee34b8cbc097d1547b41001e5bf9777a
http://arxiv.org/abs/2007.15724
http://arxiv.org/abs/2007.15724
Publikováno v:
ROBIO
Loop closure is a crucial part in SLAM, especially for large and long-term scenes. Utilizing off-the-shelf networks’ features in loop closure becomes a hot spot. However, what kind of network is more suitable in loop closure and how to use their fe