Qi Si
Orcid: 0000-0001-7456-4202
According to our database1,
Qi Si
authored at least 14 papers
between 2012 and 2024.
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Bibliography
2024
3D Geometry Modeling and Safety Compliance Assessment of In-Service Roads Using Massive LiDAR Point Clouds.
IEEE Trans. Intell. Transp. Syst., June, 2024
Forecasting Chinese carbon emission intensity based on the interactive effect GM(1, N) power model.
Grey Syst. Theory Appl., 2024
Robust kernel-free quadratic surface twin support vector machine with capped L<sub>1</sub>-norm distance metric.
CoRR, 2024
DeepMRA: An Efficient Microservices Resource Allocation Framework with Deep Reinforcement Learning in the Cloud.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2024
2023
Symmetric LINEX loss twin support vector machine for robust classification and its fast iterative algorithm.
Neural Networks, November, 2023
2022
Deep Feature-Review Transmit Network of Contour-Enhanced Road Extraction From Remote Sensing Images.
IEEE Geosci. Remote. Sens. Lett., 2022
DeepLRA: An Efficient Long Running Application Scheduling Framework with Deep Reinforcement Learning in the Cloud.
Proceedings of the PRICAI 2023: Trends in Artificial Intelligence, 2022
2020
Coarse-to-Fine Classification of Road Infrastructure Elements from Mobile Point Clouds Using Symmetric Ensemble Point Network and Euclidean Cluster Extraction.
Sensors, 2020
Multi-Armed Bandit Based Task Offloading By Probabilistic V2X Communication in Vehicle Edge Cloud System.
Proceedings of the 91st IEEE Vehicular Technology Conference, 2020
Network Selection in Heterogeneous Vehicular Network: A One-to-Many Matching Approach.
Proceedings of the 91st IEEE Vehicular Technology Conference, 2020
2017
IEEE Geosci. Remote. Sens. Lett., 2017
Embedded protocols based on the crowd Petri networks and opportunistic bandwidth allocation.
EURASIP J. Embed. Syst., 2017
Mechanical hydraulic characteristic analysis scheme based on lightweight crowd data in mobile embedded devices.
EURASIP J. Embed. Syst., 2017
2012
Research on comprehensive carrying capacity assessment method with data-driven neural network.
Proceedings of the Eighth International Conference on Natural Computation, 2012