Suchergebnisse - "Big data in robotics and automation"

Long-Short Term Spatiotemporal Tensor Prediction for Passenger Flow Profile

Autoren: Ziyue Li Hao Yan Chen Zhang et al.

Quelle: IEEE Robotics and Automation Letters. 5:5010-5017

Schlagwörter: Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Science - Machine Learning, Big data in robotics and automation, FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, Applications (stat.AP), 02 engineering and technology, Intelligent transportation system, Electrical Engineering and Systems Science - Signal Processing, Probability and statistical methods, Statistics - Applications, Machine Learning (cs.LG)

Zugangs-URL: http://arxiv.org/pdf/2004.11022
http://arxiv.org/abs/2004.11022
https://ieeexplore.ieee.org/document/9126133
https://dblp.uni-trier.de/db/journals/corr/corr2004.html#abs-2004-11022
http://ieeexplore.ieee.org/document/9126133
https://doi.org/10.1109/LRA.2020.3004785
http://ui.adsabs.harvard.edu/abs/2020arXiv200411022L/abstract
http://dblp.uni-trier.de/db/journals/ral/ral5.html#LiYZT20

Federated Imitation Learning: A Novel Framework for Cloud Robotic Systems With Heterogeneous Sensor Data

Autoren: Boyi Liu Lujia Wang Ming Liu et al.

Quelle: IEEE Robotics and Automation Letters. 5:3509-3516

Schlagwörter: FOS: Computer and information sciences, Computer Science - Machine Learning, 0209 industrial biotechnology, Big data in robotics and automation, Computer Science - Artificial Intelligence, Computational modeling, 02 engineering and technology, Microstrip, Machine Learning (cs.LG), Computer Science - Robotics, Artificial Intelligence (cs.AI), Deep learning in robotics and automation, Motion and path planning, Robot sensing systems, Task analysis, Fuses, Cloud computing, Robotics (cs.RO)

Zugangs-URL: http://arxiv.org/pdf/1912.12204
http://arxiv.org/abs/1912.12204
http://ieeexplore.ieee.org/document/9013081/
https://dblp.uni-trier.de/db/journals/corr/corr1912.html#abs-1912-12204
https://ieeexplore.ieee.org/document/9013081/
https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002274053393025
http://dblp.uni-trier.de/db/journals/ral/ral5.html#LiuWLX20

Ground Segmentation From Large-Scale Terrestrial Laser Scanner Data of Industrial Environments

Autoren: Giorgini, M. BARBIERI, FEDERICO Aleotti, J. et al.

Weitere Verfasser: Giorgini, M. BARBIERI, FEDERICO Aleotti, J. et al.

Quelle: IEEE Robotics and Automation Letters. 2:1948-1955

Schlagwörter: 0209 industrial biotechnology, Big Data in robotics and automation, segmentation, factory automation, 0202 electrical engineering, electronic engineering, information engineering, range sensing, object detection, 02 engineering and technology, categorization, logistic

Zugangs-URL: https://ieeexplore.ieee.org/document/7949103/
https://dblp.uni-trier.de/db/journals/ral/ral2.html#GiorginiBA17
http://dblp.uni-trier.de/db/journals/ral/ral2.html#GiorginiBA17
http://ieeexplore.ieee.org/document/7949103/

Effects of Extended Stochastic Gradient Descent Algorithms on Improving Latent Factor-Based Recommender Systems

Autoren: Luo, Xin Zhou, Mengchu

Quelle: Faculty Publications

Schlagwörter: AI-based methods, Big data in robotics and automation, machine learning

Relation: https://digitalcommons.njit.edu/fac_pubs/7704

Verfügbarkeit: https://digitalcommons.njit.edu/fac_pubs/7704
https://doi.org/10.1109/LRA.2019.2891986

Federated Imitation Learning: A Novel Framework for Cloud Robotic Systems With Heterogeneous Sensor Data

Autoren: Liu, Boyi Wang, Lujia Liu, Ming et al.

Index Begriffe: Cloud computing, Robot sensing systems, Task analysis, Fuses, Microstrip, Computational modeling, Big data in robotics and automation, Deep learning in robotics and automation, Motion and path planning, Article

URL: http://repository.ust.hk/ir/Record/1783.1-103753
http://lbdiscover.ust.hk/uresolver?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rfr_id=info:sid/HKUST:SPI&rft.genre=article&rft.issn=2377-3766&rft.volume=5&rft.issue=2&rft.date=2020&rft.spage=3509&rft.aulast=Liu&rft.aufirst=&rft.atitle=Federated%20Imitation%20Learning%3A%20A%20Novel%20Framework%20for%20Cloud%20Robotic%20Systems%20With%20Heterogeneous%20Sensor%20Data&rft.title=IEEE%20Robotics%20and%20Automation%20Letters
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http://www.scopus.com/record/display.url?eid=2-s2.0-85082392564&origin=inward