Author
Qingyuan Zeng
Bio: Qingyuan Zeng is an academic researcher from Wuhan University. The author has contributed to research in topics: Medicine & Chemistry. The author has an hindex of 1, co-authored 1 publications receiving 7 citations.
Papers
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TL;DR: The analysis of relationship between the oxidation peak potential (EOP) and the reaction rate constant indicated that photocatalysis using as prepared g-C3N4/CeO2-3 heterojunction is apt to oxidize contaminants with electron withdrawing group under acid condition.
31 citations
TL;DR: Wang et al. as discussed by the authors proposed an improved two-stage detection method based on parallel feature fusion and an adaptive threshold generation algorithm, which outperformed the existing methods, achieving the accuracy of 99.01% and 98.5% on the MICC F220 and MICC-F2000 datasets respectively.
Abstract: Abstract The copy-move forgery refers to the copying and pasting of a region of the original image into the target region of the same image, which represents a typical tampering method with the characteristics of easy tampering and high-quality tampering. The existing single feature-based methods of forgery detection have certain shortcomings, such as high false alarm rate, low robustness, and low detection accuracy. To address these shortcomings, this paper proposes an improved two-stage detection method based on parallel feature fusion and an adaptive threshold generation algorithm. Firstly, the SLIC super-pixels segmentation algorithm is used for image preprocessing, and a similar region extraction algorithm without threshold is employed to obtain the suspected tampering regions with high similarity. Secondly, the parallel fusion feature is obtained based on the SIFT and HU features to express the characteristics of local regions. Then, the corresponding threshold value is generated based on the histogram of oriented gradient (HOG) to describe the texture characteristics of the obtained regions, which acts as a criterion to judge whether a region has been forged or not. The experimental results show that the proposed method outperforms the existing methods, achieving the accuracy of 99.01% and 98.5% on the MICC-F220 and MICC-F2000 datasets respectively. In addition, the proposed method has stronger robustness performance on COMOFOD dataset than the comparison methods.
4 citations
TL;DR: Wang et al. as mentioned in this paper proposed an improved two-stage detection method based on parallel feature fusion and an adaptive threshold generation algorithm, which outperformed the existing methods, achieving the accuracy of 99.01% and 98.5% on the MICC F220 and MICC-F2000 datasets respectively.
Abstract: Abstract The copy-move forgery refers to the copying and pasting of a region of the original image into the target region of the same image, which represents a typical tampering method with the characteristics of easy tampering and high-quality tampering. The existing single feature-based methods of forgery detection have certain shortcomings, such as high false alarm rate, low robustness, and low detection accuracy. To address these shortcomings, this paper proposes an improved two-stage detection method based on parallel feature fusion and an adaptive threshold generation algorithm. Firstly, the SLIC super-pixels segmentation algorithm is used for image preprocessing, and a similar region extraction algorithm without threshold is employed to obtain the suspected tampering regions with high similarity. Secondly, the parallel fusion feature is obtained based on the SIFT and HU features to express the characteristics of local regions. Then, the corresponding threshold value is generated based on the histogram of oriented gradient (HOG) to describe the texture characteristics of the obtained regions, which acts as a criterion to judge whether a region has been forged or not. The experimental results show that the proposed method outperforms the existing methods, achieving the accuracy of 99.01% and 98.5% on the MICC-F220 and MICC-F2000 datasets respectively. In addition, the proposed method has stronger robustness performance on COMOFOD dataset than the comparison methods.
4 citations
TL;DR: Deep learning with CNN based on IVIM-DWI can be conducive to preoperative prediction of MVI in patients with HCC, and the fusion model combined with deep features of IVIM, clinical characteristics, and ADC yields better performance for predicting MVI than the model only based onIVIM.
4 citations
TL;DR: This study aimed to investigate the role of circ_0119412 whose function was not explored in cervical cancer, and mounting evidence summarizes that circRNA is closely implicated in the development of numerous cancers.
Abstract: Mounting evidence summarizes that circRNA is closely implicated in the development of numerous cancers. Our study aimed to investigate the role of circ_0119412 whose function was not explored in cervical cancer.
3 citations
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TL;DR: In this article, the authors provide deep insights on heterojunction mechanisms and the latest progress on photodegradation of various contaminants in wastewater using CeO2-based photocatalysts.
93 citations
TL;DR: In this article , the authors provide deep insights on heterojunction mechanisms and the latest progress on photodegradation of various contaminants in wastewater using CeO2-based photocatalysts.
91 citations
TL;DR: In this paper, the effect of different amounts of Ag nanocrystals adsorbed on the surfaces of Au@Cu2O on the surface-enhanced Raman scattering (SERS) activity was investigated based on the SERS detection of 4-mercaptobenzoic acid (4-MBA) reporter molecules.
Abstract: Ternary noble metal-semiconductor nanocomposites (NCs) with core-shell-satellite nanostructures have received widespread attention due to their outstanding performance in detecting pollutants through surface-enhanced Raman scattering (SERS) and photodegradation of organic pollutants. In this work, ternary Au@Cu2O-Ag NCs were designed and prepared by a galvanic replacement method. The effect of different amounts of Ag nanocrystals adsorbed on the surfaces of Au@Cu2O on the SERS activity was investigated based on the SERS detection of 4-mercaptobenzoic acid (4-MBA) reporter molecules. Based on electromagnetic field simulations and photoluminescence (PL) results, a possible SERS enhancement mechanism was proposed and discussed. Moreover, Au@Cu2O-Ag NCs served as SERS substrates, and highly sensitive SERS detection of malachite green (MG) with a detection limit as low as 10-9 M was achieved. In addition, Au@Cu2O-Ag NCs were recycled due to their superior self-cleaning ability and could catalyze the degradation of MG driven by visible light. This work demonstrates a wide range of possibilities for the integration of recyclable SERS detection and photodegradation of organic dyes and promotes the development of green testing techniques.
53 citations
TL;DR: In this paper, mesoporous nanosheets assembled microspheres (D-CeO2) are engineered by polymer precipitation, hydrothermal and surface hydrogenation strategies.
23 citations
TL;DR: In this paper , mesoporous nanosheets assembled microspheres (D-CeO2) are engineered by polymer precipitation, hydrothermal and surface hydrogenation strategies.
20 citations