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Jinghuan Wen

dblp:13/11192 · DBLP profile ↗
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4ranked-venue papers
2as first author
0since 2021 · last 2020
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 3 · 2 first-authorComputer networks · 1

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.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 100%
Computer networks
1 paper
Internet of things and sensor networks · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Embedded and real-time systems › energy harvesting systems
energy harvesting sensor node		 0.112012
An energy harvesting nonvolatile sensor node and its application to distributed moving object detection · IPSN 2012
Embedded and real-time systems
energy harvesting systems		 0.112012
An energy harvesting nonvolatile sensor node and its application to distributed moving object detection · IPSN 2012
Embedded and real-time systems › energy harvesting systems
nonvolatile processor		 0.112012
An energy harvesting nonvolatile sensor node and its application to distributed moving object detection · IPSN 2012
YearPublicationVenuePosition
2020 Cross-Domain Disentangle Network for Image Manipulation
Zhening Xing, Jinghuan Wen, Huimin Ma 0001
 PRCV (3)2
2020 Deep generative smoke simulator: connecting simulated and real data
Jinghuan Wen, Huimin Ma 0001, Xiong Luo
 Vis. Comput.1
2019 Real-time smoke simulation based on vorticity preserving lattice Boltzmann method
Jinghuan Wen, Huimin Ma 0001
 Vis. Comput.1
2012 An energy harvesting nonvolatile sensor node and its application to distributed moving object detection
abstract
Energy harvesting sensor nodes based on real nonvolatile processors are demonstrated to show the desirable characteristics of those systems, such as no battery, zero stand-by power, microsecond-scale sleep and wake-up time, high resilience to random power failures and fine-grained power management. Furthermore, we show its applications to a distributed moving object detection system, one of novel nonvolatile computing systems.
Yongpan Liu, Hongyang Jia, Shan Su, Jinghuan Wen, Wenzhu Zhang, Lin Zhang 0001, Huazhong Yang
 IPSN5