M
Minfeng Zhu
Researcher at Zhejiang University
Publications - 34
Citations - 875
Minfeng Zhu is an academic researcher from Zhejiang University. The author has contributed to research in topics: Graph (abstract data type) & Computer science. The author has an hindex of 8, co-authored 28 publications receiving 359 citations.
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Proceedings ArticleDOI
DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-To-Image Synthesis
TL;DR: DM-GAN as mentioned in this paper introduces a dynamic memory module to refine fuzzy image contents, when the initial images are not well generated, which enables the method to accurately generate images from the text description.
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DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-to-Image Synthesis
TL;DR: The proposed DM-GAN model introduces a dynamic memory module to refine fuzzy image contents, when the initial images are not well generated, and performs favorably against the state-of-the-art approaches.
Journal ArticleDOI
EEMEFN: Low-Light Image Enhancement via Edge-Enhanced Multi-Exposure Fusion Network
TL;DR: This paper proposes a two-stage method called Edge-Enhanced Multi-Exposure Fusion Network (EEMEFN) to enhance extremely low-light images, which can reconstruct high-quality images with sharp edges when minimizing the pixel-wise loss.
Journal ArticleDOI
VAUD: A Visual Analysis Approach for Exploring Spatio-Temporal Urban Data
TL;DR: A novel visual analytics approach, Visual Analyzer for Urban Data (VAUD), that supports the visualization, querying, and exploration of urban data and allows for cross-domain correlation from multiple data sources by leveraging spatial-temporal and social inter-connectedness features.
Journal ArticleDOI
A new method of large-scale short-term forecasting of agricultural commodity prices: illustrated by the case of agricultural markets in Beijing
TL;DR: A mixed model, which combines ARIMA model and PLS regression method based on time and space factors is proposed, which is more accurate in forecasting agricultural commodity prices than each single model does, and has better accuracy in warning values.