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Ye Yuan
Researcher at Carnegie Mellon University
Publications - 3
Citations - 1950
Ye Yuan is an academic researcher from Carnegie Mellon University. The author has contributed to research in topics: Deep learning & Upsampling. The author has an hindex of 2, co-authored 2 publications receiving 1344 citations.
Papers
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Proceedings ArticleDOI
Understanding Convolution for Semantic Segmentation
TL;DR: DUC is designed to generate pixel-level prediction, which is able to capture and decode more detailed information that is generally missing in bilinear upsampling, and a hybrid dilated convolution (HDC) framework in the encoding phase is proposed.
Posted Content
Understanding Convolution for Semantic Segmentation
TL;DR: Zhang et al. as mentioned in this paper design dense upsampling convolution (DUC) to generate pixel-level prediction, which is able to capture and decode more detailed information that is generally missing in bilinear upampling.
Journal ArticleDOI
STGAN: Spatio-Temporal Generative Adversarial Network for Traffic Data Imputation
TL;DR: Wang et al. as mentioned in this paper proposed a novel spatio-temporal GAN model for the traffic data imputation, which not only minimizes the reconstructed errors of the imputed entries, but also ensures each imputed entry and its neighbors conform to the local spatiotemporal distribution.