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Libing Wang

dblp:188/7707 · DBLP profile ↗
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6ranked-venue papers
3as first author
6since 2021 · last 2025
—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2 · 2 first-author · 2 since 2021Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021Computer networks · 1 · 1 first-author · 1 since 2021Security and privacy · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Multi-agent systems · 100%
Theoretical computer science
1 paper
Mathematical optimization · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Multi-agent systems › game theory
nash equilibrium
0.912025
Distributed Nash equilibrium for pursuit-evasion game with one evader and multiple pursuers · Sci. China Inf. Sci. 2025
Knowledge, reasoning and agents › Multi-agent systems
pursuit-evasion
0.912025
Distributed Nash equilibrium for pursuit-evasion game with one evader and multiple pursuers · Sci. China Inf. Sci. 2025
Mathematical optimization
distributed optimization
0.312025
Distributed Nash equilibrium for pursuit-evasion game with one evader and multiple pursuers · Sci. China Inf. Sci. 2025
YearPublicationVenuePosition
2025 Distributed Nash equilibrium for pursuit-evasion game with one evader and multiple pursuers
Libing Wang, Zhiqiang Pu
Sci. China Inf. Sci.1
2024 Deep convolutional encoder-decoder networks based on ensemble learning for semantic segmentation of high-resolution aerial imagery
Huming Zhu, Chendi Liu, Qiuming Li, Libing Wang, Licheng Jiao, Biao Hou
CCF Trans. High Perform. Comput.5
2024 A traffic-weather generative adversarial network for traffic flow prediction for road networks under bad weather
Wensong Zhang, Ronghan Yao, Xiaojing Du, Libing Wang
Eng. Appl. Artif. Intell.5
2021 T Line and C Line Detection and Ratio Reading of the Ovulation Test Strip Based on Deep Learning
Libing Wang, Deane Zeng, Yimin Wen
IDEAL1
2021 Joint Power and Bandwidth Allocation for Internet of Vehicles Based on Proximal Policy Optimization Algorithm
abstract
With the rapid development of 5G mobile communication and intelligent vehicles, efficient and reliable vehicle-to-vehicle communication is recognized as one of the key technologies for the next generation of wireless networks in the future. Due to the rapid changes in the wireless channel due to the high mobility of vehicles, the traditional resource allocation technology is no longer suitable for the current vehicle network. This paper proposes a joint resource allocation method for the internet of vehicles communication based on the proximal policy optimization algorithm. In this paper, a joint optimization scheme of discrete and continuous resources suitable for the internet of vehicles communication is designed to effectively meet the strict requirements of vehicle-mounted communication. Simulation results show that the proposed allocation method can maximize the system capacity and satisfy the delay constraints of vehicle-to-vehicle communication.
Sujie Xu, Xin Hu 0006, Libing Wang, Weidong Wang 0001
TrustCom3
2021 Dynamic job-shop scheduling in smart manufacturing using deep reinforcement learning
Libing Wang, Xin Hu 0006, Sujie Xu, Shijun Ma, Weidong Wang 0001
Comput. Networks1