Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Shile LI"'
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 126, Iss , Pp 103616- (2024)
The soil freeze–thaw (FT) cycle is a critical component of the terrestrial cryosphere and plays a significant role in hydrological, ecological, climatic, and biogeochemical processes within permafrost landscapes. The FT states can be monitored with
Externí odkaz:
https://doaj.org/article/c64a347503a14307b8a1b1deca693047
Autor:
Lulu LIU, Wenxuan CHEN, Xiaohui LIU, Shile LI, Zhihao XU, Hongbin CHEN, Zongping ZHENG, Baobei WANG
Publikováno v:
Shipin gongye ke-ji, Vol 43, Iss 19, Pp 76-83 (2022)
To improve nutritive value and quality of chiffon cake, Haematococcus pluvialis powder was added to chiffon cake in this study. Nutrients of H. pluvialis was determined by HPLC and GC-MS. Using automatic color difference meter and texture analyser to
Externí odkaz:
https://doaj.org/article/427bc04abed34310af0afd46cdeb1634
Publikováno v:
2021 18th International Conference on Ubiquitous Robots (UR).
One way to achieve dexterous manipulation autonomously with natural input is through learning by demonstration. Unfortunately, grasping an object with a complex dexterous hand is a complicated task. To facilitate the demo acquisition process, we prop
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7fc3579e0fa72cd52bcea2197f5b4a21
https://doi.org/10.1109/ur52253.2021.9494665
https://doi.org/10.1109/ur52253.2021.9494665
Publikováno v:
ICRA
Hand pose estimation with objects is challenging due to object occlusion and the lack of large annotated datasets. To tackle these issues, we propose an Augmented Autoencoder based deep learning method using augmented clean hand data. Our method take
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::66ac2210243bad1c23cd3b5b39c7728b
https://doi.org/10.1109/icra40945.2020.9197299
https://doi.org/10.1109/icra40945.2020.9197299
Autor:
Shreyas Hampali, Fu Xiong, Shipeng Xie, Zdenek Krnoul, Weiguo Zhou, Sijia Mei, Seungryul Baek, Zhaohui Zhang, Haifeng Sun, Guillermo Garcia-Hernando, Yang Xiao, Dongheui Lee, Angela Yao, Umar Iqbal, Mahdi Rad, Marek Hrúz, Adrian Spurr, Qingfu Wan, Zhiguo Cao, Junsong Yuan, Vincent Lepetit, Pavlo Molchanov, Romain Brégier, Pengfei Ren, Yunhui Liu, Shile Li, Philippe Weinzaepfel, Linlin Yang, Anil Armagan, Weiting Huang, Grégory Rogez, Boshen Zhang, Tae-Kyun Kim, Mingxiu Chen, Jakub Kanis
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585914
ECCV (23)
ECCV (23)
We study how well different types of approaches generalise in the task of 3D hand pose estimation under single hand scenarios and hand-object interaction. We show that the accuracy of state-of-the-art methods can drop, and that they fail mostly on po
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::334571a0b2fa3856d677209cb23e6322
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 2, Pp 2825-2837 (2023)
Abstract 3D object detection is a critical task in the fields of virtual reality and autonomous driving. Given that each sensor has its own strengths and limitations, multi-sensor-based 3D object detection has gained popularity. However, most existin
Externí odkaz:
https://doaj.org/article/409b3f54320a48d7966fe92886bd783f
Autor:
Dongheui Lee, Shile Li
Publikováno v:
IEEE Robotics and Automation Letters. 2:2263-2270
We propose a real-time depth edge based RGB-D SLAM system for dynamic environment. Our visual odometry method is based on frame-to-keyframe registration, where only depth edge points are used. To reduce the influence of dynamic objects, we propose a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6a11bce1c7e0c353dba7c6e6c482f3fd
https://doi.org/10.1109/lra.2017.2724759
https://doi.org/10.1109/lra.2017.2724759
Publikováno v:
RO-MAN
Learning from Demonstrations is a promising technique to transfer task knowledge from a user to a robot. We propose a framework for task programming by observing the human hand pose and object locations solely with a depth camera. By extracting skill
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::86b21854f0d4faba7a1b46bde35f51a8
https://mediatum.ub.tum.de/doc/1584085/document.pdf
https://mediatum.ub.tum.de/doc/1584085/document.pdf