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About the database ScholarIQanswers from OpenAlex & ORCID
How has Hu Chen's publication output changed over time?
ScholarIQpublication output · 2008–2025
Output declined50% over the shown period — from 2 works in 2008 to 1 in 2025.
2
1
4
1
1
1
1
2008201420172018201920212025
What are the most-cited papers on Hu Chen?
ScholarIQmost cited works
Low-Dose CT With a Residual Encoder-Decoder Convolutional Neural Network
Hu Chen, Yi Zhang, Mannudeep K. Kalra, Feng Lin, Yang Chen, Peixi Liao, Jiliu Zhou, Ge Wang
S58069681. 20171,852 CitationsOPEN ACCESS
aLow-dose CT via convolutional neural network
Hu Chen, Yi Zhang, Weihua Zhang, Peixi Liao, Ke Li, Jiliu Zhou, Ge Wang
S104118869. 2017757 CitationsOPEN ACCESS
LEARN: Learned Experts’ Assessment-Based Reconstruction Network for Sparse-Data CT
Hu Chen, Yi Zhang, Yunjin Chen, Junfeng Zhang, Weihua Zhang, Huaiqiang Sun, Yang Lv, Peixi Liao, Jiliu Zhou, Ge Wang
S58069681. 2018443 CitationsOPEN ACCESS
SUPERMASSIVE BLACK HOLES WITH HIGH ACCRETION RATES IN ACTIVE GALACTIC NUCLEI. I. FIRST RESULTS FROM A NEW REVERBERATION MAPPING CAMPAIGN
Pu Du, Hu Chen, Kai-Xing Lu, Fang Wang, J. F. Qiu, Yanrong Li, Jin-Ming Bai, S. Kaspi, Hagai Netzer, Jian‐Min Wang
S1980519. 2014239 CitationsOPEN ACCESS
Denoising of 3D magnetic resonance images using a residual encoder–decoder Wasserstein generative adversarial network
Maosong Ran, Jinrong Hu, Yang Chen, Hu Chen, Huaiqiang Sun, Jiliu Zhou, Yi Zhang
S116571295. 2019171 Citations
Related on ScholarIQ
Kunming University of Science and Technology
Institution
Low-Dose CT With a Residual Encoder-Decoder Convolutional Neural Network
Paper
aLow-dose CT via convolutional neural network
Paper
LEARN: Learned Experts’ Assessment-Based Reconstruction Network for Sparse-Data CT
Paper
SUPERMASSIVE BLACK HOLES WITH HIGH ACCRETION RATES IN ACTIVE GALACTIC NUCLEI. I. FIRST RESULTS FROM A NEW REVERBERATION MAPPING CAMPAIGN
Paper
Denoising of 3D magnetic resonance images using a residual encoder–decoder Wasserstein generative adversarial network
Paper