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450 results on '"Yue, Xiaodong"'

1. Safe Data Resampling Method Based on Counterfactuals Analysis

Author

Liu, Diwen, Yue, Xiaodong, Xu, Zhikang, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Wand, Michael, editor, Malinovská, Kristína, editor, Schmidhuber, Jürgen, editor, and Tetko, Igor V., editor

Published
2024
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2. Cross-Weighting Knowledge Distillation for Object Detection

Author

Li, Zhaoyi, Li, Zihao, Yue, Xiaodong, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Hu, Mengjun, editor, Cornelis, Chris, editor, Zhang, Yan, editor, Lingras, Pawan, editor, Ślęzak, Dominik, editor, and Yao, JingTao, editor

Published
2024
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8. Evidence Reconciled Neural Network for Out-of-Distribution Detection in Medical Images

Author

Fu, Wei, Chen, Yufei, Liu, Wei, Yue, Xiaodong, Ma, Chao, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Greenspan, Hayit, editor, Madabhushi, Anant, editor, Mousavi, Parvin, editor, Salcudean, Septimiu, editor, Duncan, James, editor, Syeda-Mahmood, Tanveer, editor, and Taylor, Russell, editor

Published
2023
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9. Deep Determinantal Q-Learning with Role Aware

Author

Han, Kai, Yue, Xiaodong, Liu, Wei, Zhan, Jinxin, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Fujita, Hamido, editor, Wang, Yinglin, editor, Xiao, Yanghua, editor, and Moonis, Ali, editor

Published
2023
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10. Accelerating Deep Reinforcement Learning with Fuzzy Logic Rules

Author

Zhan, Jinxin, Yue, Xiaodong, Li, Zihao, Han, Kai, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Fujita, Hamido, editor, Wang, Yinglin, editor, Xiao, Yanghua, editor, and Moonis, Ali, editor

Published
2023
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11. Convolutional Redistribution Network for Multi-view Medical Image Diagnosis

Author

Zhou, Yuan, Yue, Xiaodong, Chen, Yufei, Ma, Chao, Jiang, Ke, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chen, Yufei, editor, Linguraru, Marius George, editor, Shekhar, Raj, editor, Wesarg, Stefan, editor, Erdt, Marius, editor, Drechsler, Klaus, editor, and Oyarzun Laura, Cristina, editor

Published
2023
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14. Granular conditional entropy-based attribute reduction for partially labeled data with proxy labels

Author

Gao, Can, Zhoua, Jie, Miao, Duoqian, Yue, Xiaodong, and Wan, Jun

Subjects
Computer Science - Artificial Intelligence
Abstract

Attribute reduction is one of the most important research topics in the theory of rough sets, and many rough sets-based attribute reduction methods have thus been presented. However, most of them are specifically designed for dealing with either labeled data or unlabeled data, while many real-world applications come in the form of partial supervision. In this paper, we propose a rough sets-based semi-supervised attribute reduction method for partially labeled data. Particularly, with the aid of prior class distribution information about data, we first develop a simple yet effective strategy to produce the proxy labels for unlabeled data. Then the concept of information granularity is integrated into the information-theoretic measure, based on which, a novel granular conditional entropy measure is proposed, and its monotonicity is proved in theory. Furthermore, a fast heuristic algorithm is provided to generate the optimal reduct of partially labeled data, which could accelerate the process of attribute reduction by removing irrelevant examples and excluding redundant attributes simultaneously. Extensive experiments conducted on UCI data sets demonstrate that the proposed semi-supervised attribute reduction method is promising and even compares favourably with the supervised methods on labeled data and unlabeled data with true labels in terms of classification performance., Comment: 22 pages, 5 figures, and 5 tables. Preprint submitted to Information Sciences

Published
2021

16. Uncertainty-Aware Deep Open-Set Object Detection

Author

Hang, Qi, Li, Zihao, Dong, Yudi, Yue, Xiaodong, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Yao, JingTao, editor, Fujita, Hamido, editor, Yue, Xiaodong, editor, Miao, Duoqian, editor, Grzymala-Busse, Jerzy, editor, and Li, Fanzhang, editor

Published
2022
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17. Video Object Detection with MeanShift Tracking

Author

Zhang, Shuai, Liu, Wei, Fu, Haijie, Yue, Xiaodong, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Yao, JingTao, editor, Fujita, Hamido, editor, Yue, Xiaodong, editor, Miao, Duoqian, editor, Grzymala-Busse, Jerzy, editor, and Li, Fanzhang, editor

Published
2022
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19. Cultural Differences in the Hedonic Rewards of Recalling Kindness: Priming Cultural Identity with Language

Author

Shin, Lilian J, Margolis, Seth M, Walsh, Lisa C, Kwok, Sylvia YCL, Yue, Xiaodong, Chan, Chi-Keung, Siu, Nicolson Yat-Fan, Sheldon, Kennon M, and Lyubomirsky, Sonja

Subjects
Culture, Emotion, Kind acts, Priming, Well-being
Abstract

Recent theory suggests that members of interdependent (collectivist) cultures prioritize in-group happiness, whereas members of independent (individualist) cultures prioritize personal happiness (Uchida et al. Journal of Happiness Studies, 5(3), 223-239 Uchida et al., 2004). Thus, the well-being of friends and family may contribute more to the emotional experience of individuals with collectivist rather than individualist identities. We tested this hypothesis by asking participants to recall a kind act they had done to benefit either close others (e.g., family members) or distant others (e.g., strangers). Study 1 primed collectivist and individualist cultural identities by asking bicultural undergraduates (N = 357) from Hong Kong to recall kindnesses towards close versus distant others in both English and Chinese, while Study 2 compared university students in the USA (n = 106) and Hong Kong (n = 93). In Study 1, after being primed with the Chinese language (but not after being primed with English), participants reported significantly improved affect valence after recalling kind acts towards friends and family than after recalling kind acts towards strangers. Extending this result, in Study 2, respondents from Hong Kong (but not the USA) who recalled kind acts towards friends and family showed higher positive affect than those who recalled kind acts towards strangers. These findings suggest that people with collectivist cultural identities may have relatively more positive and less negative emotional experiences when they focus on prosocial interactions with close rather than weak ties.Supplementary informationThe online version contains supplementary material available at 10.1007/s42761-020-00029-3.

Published
2021

22. Harnessing Deep Bladder Tumor Segmentation with Logical Clinical Knowledge

Author

Huang, Xiao, Yue, Xiaodong, Xu, Zhikang, Chen, Yufei, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Wang, Linwei, editor, Dou, Qi, editor, Fletcher, P. Thomas, editor, Speidel, Stefanie, editor, and Li, Shuo, editor

Published
2022
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30. Multi-branch Recurrent Attention Convolutional Neural Network with Evidence Theory for Fine-Grained Image Classification

Author

Xu, Zhikang, Zhang, Bofeng, Fu, Haijie, Yue, Xiaodong, Lv, Ying, 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, Denœux, Thierry, editor, Lefèvre, Eric, editor, Liu, Zhunga, editor, and Pichon, Frédéric, editor

Published
2021
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31. Deep Evidential Fusion Network for Image Classification

Author

Xu, Shaoxun, Chen, Yufei, Ma, Chao, Yue, Xiaodong, 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, Denœux, Thierry, editor, Lefèvre, Eric, editor, Liu, Zhunga, editor, and Pichon, Frédéric, editor

Published
2021
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32. Ensemble of Adapters for Transfer Learning Based on Evidence Theory

Author

Lv, Ying, Zhang, Bofeng, Yue, Xiaodong, Xu, Zhikang, Liu, Wei, 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, Denœux, Thierry, editor, Lefèvre, Eric, editor, Liu, Zhunga, editor, and Pichon, Frédéric, editor

Published
2021
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33. Adolescents' loneliness and problematic smartphone use: The mediating role of upward social comparison and the moderating role of self‐identity.

Author

Shao, Siyang, Mao, Ningning, Zhang, Zhengtian, Yang, Mo, He, Siyu, Yue, Xiaodong, Li, Chieh, and Cui, Lixia

Subjects
LONELINESS, SOCIAL comparison, IDENTITY (Psychology), SMARTPHONES, CHINESE people, TEENAGERS
Abstract

Loneliness is an important risk factor for problematic smartphone use (PSU) among adolescents and the mechanisms underlying this correlation remain unclear. In this study, a moderated serial mediation model was tested by administering the Problematic Smartphone Use Scale for Chinese Adolescents, the Loneliness Scale (LS), the Upward Social Comparison Scale, the Fear of Missing Out Scale, and the Self‐Identity Scale to 466 Chinese adolescents. The results showed that: (1) loneliness was positively correlated with PSU, (2) upward social comparison (USC) and fear of missing out served as sequential mediating factors in the correlation between loneliness and PSU, and (3) self‐identity played a moderating role between USC and fear of missing out. These findings shed new light on developing strategies to prevent and intervene in adolescents' PSU by revealing the underlying mechanisms between loneliness and PSU. Practitioner Points: Loneliness is a key factor in problematic smartphone use (PSU) among adolescents.Reducing upward social comparison (USC) and the fear of missing out (FOMO) may deter lonely adolescents from PSU.Strengthening adolescents' self‐identity may help weaken the link between USC and FOMO. [ABSTRACT FROM AUTHOR]

Published
2024
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37. Clustering Ensemble Selection with Analytic Hierarchy Process

Author

Liu, Wei, Yue, Xiaodong, Zhong, Caiming, Zhou, Jie, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Yang, Haiqin, editor, Pasupa, Kitsuchart, editor, Leung, Andrew Chi-Sing, editor, Kwok, James T., editor, Chan, Jonathan H., editor, and King, Irwin, editor

Published
2020
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38. Evidential Deep Neural Networks for Uncertain Data Classification

Author

Yuan, Bin, Yue, Xiaodong, Lv, Ying, Denoeux, Thierry, 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, Li, Gang, editor, Shen, Heng Tao, editor, Yuan, Ye, editor, Wang, Xiaoyang, editor, Liu, Huawen, editor, and Zhao, Xiang, editor

Published
2020
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41. Effect of steel fiber on impact resistance and durability of concrete containing nano-SiO2

Author

Zhang Peng, Zhang Hongsen, Cui Guo, Yue Xiaodong, Guo Jinjun, and Hui David

Subjects
concrete, impact resistance, durability, steel fiber, nano-sio2, Technology, Chemical technology, TP1-1185, Physical and theoretical chemistry, QD450-801
Abstract

Impact drop weight tests, rapid chloride migration coefficient tests, single-sided freeze–thaw tests, and mechanical property tests were performed to investigate the effect of the steel fiber (SF) content on the impact resistance and durability of concrete containing nano-SiO2 (NS). A fixed NS content of 3% and six SF contents in a range of 0–2.5% by volume were used. The impact resistance was measured based on the number of blows (N1, N2) and the impact energy. The durability of concrete includes its freeze–thaw resistance and chloride ion penetration resistance, which were appraised by the chloride ion diffusion coefficient (CDC) and relative dynamic elastic modulus (RDM), respectively. The ductility ratio was used to predict the impact resistance of concrete containing NS with different SF contents, and a linear relation between this ratio and the impact energy (R 2 = 0.853) was found. The experimental results indicated that SF could greatly improve the impact resistance of concrete. The addition of 2.0% SF increased N1 and N2 by 106 and 169%, respectively. In addition, an appropriate SF content significantly improved the durability of the concrete, including its frost resistance (especially in the middle and late freezing–thawing cycles) and chloride ion penetration resistance. An SF content of 1.5% was the optimum, decreasing the CDC of nano-concrete by 17.1% and minimizing the RDM loss. Moreover, the 1.5% SF content increased the compressive strength of concrete containing NS by 18.5%, whereas an SF content of 2.0% increased the splitting tensile strength and flexural strength by 77 and 20%, respectively. Furthermore, when the SF content exceeded a certain value, the improvement effect on these properties began to decrease and even became negative.

Published
2021
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43. Typicality-Aware Adaptive Similarity Matrix for Unsupervised Learning

Author

Zhou, Jie, Gao, Can, Wang, Xizhao, Lai, Zhihui, Wan, Jun, and Yue, Xiaodong

Abstract

Graph-based clustering approaches, especially the family of spectral clustering, have been widely used in machine learning areas. The alternatives usually engage a similarity matrix that is constructed in advance or learned from a probabilistic perspective. However, unreasonable similarity matrix construction inevitably leads to performance degradation, and the sum-to-one probability constraints may make the approaches sensitive to noisy scenarios. To address these issues, the notion of typicality-aware adaptive similarity matrix learning is presented in this study. The typicality (possibility) rather than the probability of each sample being a neighbor of other samples is measured and adaptively learned. By introducing a robust balance term, the similarity between any pairs of samples is only related to the distance between them, yet it is not affected by other samples. Therefore, the impact caused by the noisy data or outliers can be alleviated, and meanwhile, the neighborhood structures can be well captured according to the joint distance between samples and their spectral embeddings. Moreover, the generated similarity matrix has block diagonal properties that are beneficial to correct clustering. Interestingly, the results optimized by the typicality-aware adaptive similarity matrix learning share the common essence with the Gaussian kernel function, and the latter can be directly derived from the former. Extensive experiments on synthetic and well-known benchmark datasets demonstrate the superiority of the proposed idea when comparing with some state-of-the-art methods.

Published
2024
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45. Fabric Texture Removal with Deep Convolutional Neural Networks

Author

Hou, Li, Yue, Xiaodong, Xiao, Xiao, Xu, Wei, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, and Wong, Wai Keung, editor

Published
2019
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46. Fabric Defect Detection with Cartoon–Texture Decomposition

Author

Lv, Ying, Yue, Xiaodong, Chen, Qiang, Wang, Meiqian, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, and Wong, Wai Keung, editor

Published
2019
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47. Fashion Style Recognition with Graph-Based Deep Convolutional Neural Networks

Author

Zhang, Cheng, Yue, Xiaodong, Liu, Wei, Gao, Can, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, and Wong, Wai Keung, editor

Published
2019
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48. Clustering Ensemble Selection with Determinantal Point Processes

Author

Liu, Wei, Yue, Xiaodong, Zhong, Caiming, Zhou, Jie, 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, Gedeon, Tom, editor, Wong, Kok Wai, editor, and Lee, Minho, editor

Published
2019
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