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Yayun Wang

dblp:117/2549 · DBLP profile ↗
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5ranked-venue papers
0as first author
3since 2021 · last 2026
—ORCID · conflict

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

Artificial intelligence and machine learning · 3 · 2 since 2021Graphics, computer vision, multimedia, augmented reality and games · 2 · 1 since 2021Computer 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.

Artificial intelligence
1 paper
Video understanding and tracking · 50% Transfer learning and domain adaptation · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Transfer learning and domain adaptation › few-shot learning
matching network
0.412020
PG-Net: Pixel to Global Matching Network for Visual Tracking · ECCV (22) 2020
Computer vision › Video understanding and tracking
object tracking
0.412020
PG-Net: Pixel to Global Matching Network for Visual Tracking · ECCV (22) 2020

Methods — techniques the papers use, named apart from their topics

pixel-to-global matching · 0.4
YearPublicationVenuePosition
2026 Reference-aware image harmonization
Hongling Gu, Bolun Zheng, Qianyu Zhang 0002, Canjin Wang, Yayun Wang, Zongpeng Li
Neural Networks6
2026 Position-Sensitive painterly image harmonization
Bolun Zheng, Qianyu Zhang 0002, Canjin Wang, Yayun Wang, Heng Jin, Qiankun Li 0005, Guodao Zhang, Zongpeng Li
Neural Networks5
2024 BG-Net: boundary-guidance network for object consistency maintaining in semantic segmentation
Xiji Cheng, Shiliang Huang, Bingyan Liao, Yayun Wang
Vis. Comput.4
2020 PG-Net: Pixel to Global Matching Network for Visual Tracking
Bingyan Liao, Chenye Wang, Yayun Wang, Yaonong Wang
ECCV (22)3
2017 Cost-Efficient Resource Allocation in Cloud Radio Access Networks With Heterogeneous Fronthaul Expenditures
abstract
As an advanced paradigm, the cloud radio access network (C-RAN) promises high spectral efficiency (SE) and energy efficiency (EE). However, the capacity-constrained front-haul has become a key performance bottleneck in C-RANs. Besides SE and EE metrics, the cost related to different kinds of fronthaul is another major concern for operators. In this paper, an economical SE (ESE) metric is proposed to jointly take traditional EE and the impact of wired/wireless fronthaul cost into account. Aiming to maximize ESE, a non-convex beamformer design problem with fronthaul capacity and transmit power constraints is formulated, and an algorithm containing outer and inner loops is proposed to deal with this non-convexity. In particular, in the outer loop, the bisection search method is adopted to transform the primal problem into an equivalent subproblem; while in the inner loop, owing to the equivalence between the subproblem and the weighted sum rate, the subproblem is solved by the weighted minimum mean square error approach. Simulation results demonstrate that the proposed ESE is more reasonable than SE and EE for the fronthaul-constrained C-RAN. Furthermore, the proposed optimization solution can significantly improve ESE, in which the impact of fronthaul cost on ESE is evaluated.
Mugen Peng, Yayun Wang, Tian Dang, Zhipeng Yan
IEEE Trans. Wirel. Commun.2