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518 results on '"Zhang, Cuicui"'

8. Joint Face Completion and Super-resolution using Multi-scale Feature Relation Learning

Author

Liu, Zhilei, Wu, Yunpeng, Li, Le, Zhang, Cuicui, and Wu, Baoyuan

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Previous research on face restoration often focused on repairing a specific type of low-quality facial images such as low-resolution (LR) or occluded facial images. However, in the real world, both the above-mentioned forms of image degradation often coexist. Therefore, it is important to design a model that can repair LR occluded images simultaneously. This paper proposes a multi-scale feature graph generative adversarial network (MFG-GAN) to implement the face restoration of images in which both degradation modes coexist, and also to repair images with a single type of degradation. Based on the GAN, the MFG-GAN integrates the graph convolution and feature pyramid network to restore occluded low-resolution face images to non-occluded high-resolution face images. The MFG-GAN uses a set of customized losses to ensure that high-quality images are generated. In addition, we designed the network in an end-to-end format. Experimental results on the public-domain CelebA and Helen databases show that the proposed approach outperforms state-of-the-art methods in performing face super-resolution (up to 4x or 8x) and face completion simultaneously. Cross-database testing also revealed that the proposed approach has good generalizability.

Published
2020

10. Facial Expression Restoration Based on Improved Graph Convolutional Networks

Author

Liu, Zhilei, Li, Le, Wu, Yunpeng, and Zhang, Cuicui

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Facial expression analysis in the wild is challenging when the facial image is with low resolution or partial occlusion. Considering the correlations among different facial local regions under different facial expressions, this paper proposes a novel facial expression restoration method based on generative adversarial network by integrating an improved graph convolutional network (IGCN) and region relation modeling block (RRMB). Unlike conventional graph convolutional networks taking vectors as input features, IGCN can use tensors of face patches as inputs. It is better to retain the structure information of face patches. The proposed RRMB is designed to address facial generative tasks including inpainting and super-resolution with facial action units detection, which aims to restore facial expression as the ground-truth. Extensive experiments conducted on BP4D and DISFA benchmarks demonstrate the effectiveness of our proposed method through quantitative and qualitative evaluations., Comment: Accepted by MMM2020

Published
2019
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11. Relation Modeling with Graph Convolutional Networks for Facial Action Unit Detection

Author

Liu, Zhilei, Dong, Jiahui, Zhang, Cuicui, Wang, Longbiao, and Dang, Jianwu

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Most existing AU detection works considering AU relationships are relying on probabilistic graphical models with manually extracted features. This paper proposes an end-to-end deep learning framework for facial AU detection with graph convolutional network (GCN) for AU relation modeling, which has not been explored before. In particular, AU related regions are extracted firstly, latent representations full of AU information are learned through an auto-encoder. Moreover, each latent representation vector is feed into GCN as a node, the connection mode of GCN is determined based on the relationships of AUs. Finally, the assembled features updated through GCN are concatenated for AU detection. Extensive experiments on BP4D and DISFA benchmarks demonstrate that our framework significantly outperforms the state-of-the-art methods for facial AU detection. The proposed framework is also validated through a series of ablation studies., Comment: Accepted by MMM2020

Published
2019
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23. Effect of air gap under bolus on superficial dose and depth of dose maximum during radiotherapy

Author

PANG Ya, LIAO Changju, ZHANG Cuicui, WEN Xiaoping, CHEN Xiaomei, and WANG Dong

Subjects
bolus, air gap, radiotherapy, surface dose, maximum dose depth, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

To explore the influence of the air gap under bolus on the superficial dose and the maximum dose depth during radiotherapy for superficial tumors. A 30 cm×30 cm×30 cm phantom and an adjacent 10 mm-thick bolus were created in the Eclipse treatment planning system (TPS). The bolus and phantom materials were set as water. The gaps between the bolus and phantom were set as 0 mm, 2 mm, 5 mm, 10 mm, 20 mm, and 30 mm-thick air. The source skin distance was set as 100 cm, while the field sizes were set as 5 cm×5 cm, 10 cm×10 cm, 15 cm×15 cm, 20 cm×20 cm, and 25 cm×25 cm. The dose (Ds) at a depth of 1 mm on the superficial surface and the depth value (dmax) of the maximum dose point in the phantom were obtained under different air gaps and field sizes. A PTW water tank was used to measure the Ds and dmax under the same conditions as the TPS on the Varian Trilogy linear accelerator, the superficial dose Ds was measured with the EBT3 film, and the ionization chamber was used to obtain dmax. The TPS and experimental measurement results were then compared. The results showed that the Ds from the TPS was 0 when there was no bolus, while the dose from the measurement was not 0. The TPS and measurement results showed that when the field size was 5 cm×5 cm, Ds decreased the fastest with the increase in air gap thickness. When the field size was 15 cm×15 cm or above, the change in Ds with the air gap thickness was relatively stable. The TPS and experimental measurement results showed that dmax was the largest without a bolus. The change in dmax in the TPS was relatively stable with an increase in air gap thickness. The experimental results showed that when the field size was 10 cm×10 cm or smaller, dmax changed more significantly as the air gap thickness increased. When the field size was 15 cm×15 cm or larger, dmax remained relatively stable as the air gap thickness increased. The TPS and experimental measurement results showed that the smaller the field size, the larger the dmax, except for large differences in Ds between them when there was no bolus. The differences in Ds of the other field sizes and air gap thicknesses were all close to 0. The overall differences between the TPS and the experimental measurement dmax values were large for different air gap thicknesses. The differences were larger for small field sizes than for large field sizes, and when the air gap thickness was 0 mm, the difference in dmax for all field sizes was the closest to 0. The TPS and experimental measurement results showed that a bolus with an underlying 0-mm air gap is needed during superficial tumor radiotherapy.

Published
2021
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27. The Changing Bohai and Yellow Seas: A Physical View

Author

Wei, Hao, Zhang, Haiyan, Yang, Wei, Feng, Jianlong, Zhang, Cuicui, Ip, Wing-Huen, Editor-in-Chief, Ando, Masataka, Series Editor, Chen, Chen-Tung Arthur, Series Editor, Di, Kaichang, Series Editor, Gan, Jianping, Series Editor, Liu, Philip L.-F., Series Editor, Lo, Ching-Hua, Series Editor, Slavin, James A., Series Editor, Zhang, Keke, Series Editor, Deshpande, R. D., Series Editor, Jull, A. J. Timothy, Series Editor, and Guo, Xinyu, editor

Published
2020
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28. Relation Modeling with Graph Convolutional Networks for Facial Action Unit Detection

Author

Liu, Zhilei, Dong, Jiahui, Zhang, Cuicui, Wang, Longbiao, Dang, Jianwu, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Ro, Yong Man, editor, Cheng, Wen-Huang, editor, Kim, Junmo, editor, Chu, Wei-Ta, editor, Cui, Peng, editor, Choi, Jung-Woo, editor, Hu, Min-Chun, editor, and De Neve, Wesley, editor

Published
2020
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29. Facial Expression Restoration Based on Improved Graph Convolutional Networks

Author

Liu, Zhilei, Li, Le, Wu, Yunpeng, Zhang, Cuicui, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Ro, Yong Man, editor, Cheng, Wen-Huang, editor, Kim, Junmo, editor, Chu, Wei-Ta, editor, Cui, Peng, editor, Choi, Jung-Woo, editor, Hu, Min-Chun, editor, and De Neve, Wesley, editor

Published
2020
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31. Research advances in abnormal lipid metabolism of lung cancer

Author

ZHANG Cuicui, QIN Tingting, MENG Zhaoting, LI Kai

Subjects
lung cancer, lipid metabolism, correlation, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Recent study has found that lipid metabolism has close relation to the occurrence, development and therapy of lung cancer and gradually becomes a hot topic in cancer cell metabolism. Analyzing the relationship between lipid metabolism and lung cancer may be helpful for accurate diagnosis, prediction of therapeutic efficacy and estimation of prognosis. Additionally, it is possible to develop drugs for tumor lipid metabolism. Therefore, this paper reviewed the characteristics of blood lipid in patients with lung cancer, their relationship to therapeutic efficacy and the medicines for lipid metabolism. This can provide reference for treatment targeting lipid metabolism in lung cancer.

Published
2021
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34. Detection of Dopamine Based on Aptamer-Modified Graphene Microelectrode.

Author

Zhang, Cuicui, Chen, Tianyou, Ying, Yiran, and Wu, Jing

Subjects
*MICROELECTRODES, *GRAPHENE, *DOPAMINE, *ELECTROCHEMICAL analysis, *DETECTION limit, *DOPING agents (Chemistry)
Abstract

In this paper, a novel aptamer-modified nitrogen-doped graphene microelectrode (Apt-Au-N-RGOF) was fabricated and used to specifically identify and detect dopamine (DA). During the synthetic process, gold nanoparticles were loaded onto the active sites of nitrogen-doped graphene fibers. Then, aptamers were modified on the microelectrode depending on Au-S bonds to prepare Apt-Au-N-RGOF. The prepared microelectrode can specifically identify DA, avoiding interference with other molecules and improving its selectivity. Compared with the N-RGOF microelectrode, the Apt-Au-N-RGOF microelectrode exhibited higher sensitivity, a lower detection limit (0.5 μM), and a wider linear range (1~100 μM) and could be applied in electrochemical analysis fields. [ABSTRACT FROM AUTHOR]

Published
2024
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35. Face Inpainting with Dynamic Structural Information of Facial Action Units

Author

Li, Le, Liu, Zhilei, Zhang, Cuicui, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Zhao, Yao, editor, Barnes, Nick, editor, Chen, Baoquan, editor, Westermann, Rüdiger, editor, Kong, Xiangwei, editor, and Lin, Chunyu, editor

Published
2019
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