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Your search keyword '"Zhu, Yapei"' showing total 7 results
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7 results on '"Zhu, Yapei"'

6. Deep Low-Rank and Piecewise-Smooth Constraint Tensor Model for Hyperspectral Anomaly Detection

Author

Feng, Maoyuan, Zhu, Yapei, Yang, Yunxiu, and Shu, Qin

Abstract

Low-rank tensor decomposition and autoencoder (AE) have recently attracted much attention in the hyperspectral anomaly detection field. Although the low-rank tensor decomposition model is self-explainable, a low-rank prior may only partially match real data. In contrast, AE can automatically learn the discriminative features between anomaly and background, whereas AE is not self-explainable. To overcome these problems, a deep low-rank and piecewise-smooth constraint tensor model is proposed for hyperspectral anomaly detection in this article, which makes full use of the low-rank and piecewise-smooth properties of the background tensor in model-driven tensor-based methods and combines the advantage of data-driven AE methods at the same time. Specifically, the background is reconstructed through the AE network, and the tensor nuclear norm (TNN) and total variation (TV) regularization are designed on the network output to make it self-explainable to exploit the low-rank and piecewise-smooth properties of the background in the 3-D. At the same time, an alternating direction method of multipliers (ADMMs)-based approach is given to solve the proposed model, making the low-rank and piecewise-smooth background tensor estimation process and the network training process into two sub-problems. Then, the background can be approximately reconstructed under the constraint of latent priors, while the anomaly is reconstructed with significant reconstruction errors. Finally, the reconstruction errors indicate the anomalous degree. Experimental results validated on several real hyperspectral datasets demonstrate the effectiveness of the proposed algorithm.

Published
2023
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7. Advanced understanding of the polybrominated diphenyl ethers (PBDEs): Insights from total environment to intoxication.

Author

Jiang L, Yang J, Yang H, Kong L, Ma H, Zhu Y, Zhao X, Yang T, and Liu W

Abstract

Polybrominated diphenyl ethers (PBDEs) are brominated compounds connected by ester bonds between two benzene rings. There are 209 congeners of PBDEs, classified according to the number and position of the bromine atoms. Due to their low cost and superior flame retardant properties, PBDEs have been extensively used as flame retardants in electronic products, plastics, textiles, and other materials since the 1970s. PBDEs are classified as persistent organic pollutants (POPs) under the Stockholm Convention because of their environmental persistence, bioaccumulation, and toxicity to both humans and wildlife. Due to their extensive use and significant quantities, PBDEs have been detected across a range of environments and biological organisms. These compounds are known to cause damage to the metabolic system, exhibit neurotoxicity, and pose reproductive hazards. This review investigates the environmental distribution and human exposure pathways of PBDEs. Using China-a country with significant PBDE use-as an example, it highlights substantial regional and temporal variations in PBDE concentrations and notes that certain environmental levels may pose risks to human health. The article then examines the toxic effects and mechanisms of PBDEs on several major target organs, summarizing recent research and the specific mechanisms underlying these toxic effects from multiple toxicological perspectives. This review enhances our understanding of PBDEs' environmental distribution, exposure pathways, and toxic mechanisms, offering valuable insights for further research and management strategies., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Published
2024
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