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1,594 results on '"Long, Jian"'

1. CLIP Multi-modal Hashing for Multimedia Retrieval

Author

Zhu, Jian, Sheng, Mingkai, Huang, Zhangmin, Chang, Jingfei, Jiang, Jinling, Long, Jian, Luo, Cheng, and Liu, Lei

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Multi-modal hashing methods are widely used in multimedia retrieval, which can fuse multi-source data to generate binary hash code. However, the individual backbone networks have limited feature expression capabilities and are not jointly pre-trained on large-scale unsupervised multi-modal data, resulting in low retrieval accuracy. To address this issue, we propose a novel CLIP Multi-modal Hashing (CLIPMH) method. Our method employs the CLIP framework to extract both text and vision features and then fuses them to generate hash code. Due to enhancement on each modal feature, our method has great improvement in the retrieval performance of multi-modal hashing methods. Compared with state-of-the-art unsupervised and supervised multi-modal hashing methods, experiments reveal that the proposed CLIPMH can significantly improve performance (a maximum increase of 8.38% in mAP)., Comment: Accepted by 31st International Conference on MultiMedia Modeling (MMM2025)

Published
2024

2. CLIP Multi-modal Hashing for Multimedia Retrieval

Author

Zhu, Jian, Sheng, Mingkai, Huang, Zhangmin, Chang, Jingfei, Jiang, Jinling, Long, Jian, Luo, Cheng, Liu, Lei, 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, Ide, Ichiro, editor, Kompatsiaris, Ioannis, editor, Xu, Changsheng, editor, Yanai, Keiji, editor, Chu, Wei-Ta, editor, Nitta, Naoko, editor, Riegler, Michael, editor, and Yamasaki, Toshihiko, editor

Published
2025
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3. Deep Prompt Multi-task Network for Abuse Language Detection

Author

Zhu, Jian, Ruan, Yuping, Chang, Jingfei, Sun, Wenhui, Wan, Hui, Long, Jian, Luo, Cheng, 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, Antonacopoulos, Apostolos, editor, Chaudhuri, Subhasis, editor, Chellappa, Rama, editor, Liu, Cheng-Lin, editor, Bhattacharya, Saumik, editor, and Pal, Umapada, editor

Published
2025
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4. Deep Prompt Multi-task Network for Abuse Language Detection

Author

Zhu, Jian, Ruan, Yuping, Chang, Jingfei, Sun, Wenhui, Wan, Hui, Long, Jian, and Luo, Cheng

Subjects
Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

The detection of abusive language remains a long-standing challenge with the extensive use of social networks. The detection task of abusive language suffers from limited accuracy. We argue that the existing detection methods utilize the fine-tuning technique of the pre-trained language models (PLMs) to handle downstream tasks. Hence, these methods fail to stimulate the general knowledge of the PLMs. To address the problem, we propose a novel Deep Prompt Multi-task Network (DPMN) for abuse language detection. Specifically, DPMN first attempts to design two forms of deep prompt tuning and light prompt tuning for the PLMs. The effects of different prompt lengths, tuning strategies, and prompt initialization methods on detecting abusive language are studied. In addition, we propose a Task Head based on Bi-LSTM and FFN, which can be used as a short text classifier. Eventually, DPMN utilizes multi-task learning to improve detection metrics further. The multi-task network has the function of transferring effective knowledge. The proposed DPMN is evaluated against eight typical methods on three public datasets: OLID, SOLID, and AbuseAnalyzer. The experimental results show that our DPMN outperforms the state-of-the-art methods., Comment: Accepted by the International Conference on Pattern Recognition (ICPR) 2024

Published
2024

5. The Characteristics and Quality of Mobile Phone Apps Targeted at Men Who Have Sex With Men in China: A Window of Opportunity for Health Information Dissemination?

Author

Yang, Guoli, Long, Jian, Luo, Dan, Xiao, Shuiyuan, and Kaminga, Atipatsa Chiwanda

Subjects
Information technology, T58.5-58.64, Public aspects of medicine, RA1-1270
Abstract

BackgroundA number of mobile phone apps has been developed specifically for men who have sex with men (MSM). We will call these mobile phone apps MSM apps for simplicity. At present, the characteristics and quality and purpose of these MSM apps are unclear. ObjectiveThe aim of this study was to objectively and comprehensively evaluate the characteristics and quality of the MSM apps to assess whether they disseminated health information among the MSM in China. MethodsWe searched 2 dominant mobile phone app stores (Apple Store and Android Market) to obtain MSM apps using the keywords MSM, gay, lesbian, gay, bisexual, and transgender (LGBT), 男同，同志，男男性接触者，同性恋，基友, and 双性恋. Apps were excluded if they did not have a Chinese language interface or if their target population was not MSM. Basic information about the eligible apps for this study, such as app name, app store category, and date of last update was gathered from the specified app stores. The quality of apps was rated by 2 independent raters using Mobile App Rating Scale (MARS). The intraclass correlation coefficient (ICC) between raters was computed as a measure for interrater reliability of the MARS. All analyses were conducted using SPSS version 20.0 (SPSS Inc). ResultsA total of 575 apps were reviewed between September 15, 2018 and September 30, 2018, out of which, 532 apps were excluded. Finally, 43 apps were included. Of the 43 apps, 16 were from the Apple Store, 10 were from Android Market, and 17 were available in both app stores. In addition, 39 out of 43 apps were for social and sexual networking, whereas 10 contained sexual health information, for example, HIV/sexually transmitted diseases knowledge, HIV test, and condom use. The average rating was 4 stars. The number of downloads for 21 apps exceeded 10,000. A total of 31 apps had acceptable quality (as defined by a MARS score of >3), with functionality as the highest scoring domain, followed by information quality, esthetics, and engagement. Interrater reliability was excellent for the overall mean app quality scores (ICC=.946; 95% CI 0.904-0.970) and the subjective quality scores (ICC=.910; 95% CI 0.841-0.950). ConclusionsBy reviewing the available apps, we found that MSM apps are popular. The majority of MSM apps are for dating, whereas few of them contain HIV prevention and health information. The overall quality of the apps is acceptable. The utilization of mobile phone technologies is a promising way for delivering HIV prevention messages to MSM. We recommend that researchers and app developers should work together to disseminate health information for MSM via mobile technologies.

Published
2019
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16. The pharmacogenomic landscape in the Chinese: An analytics of pharmacogenetic variants in 206,640 individuals

Author

Wang, Lei-Yun, Yu, Bing, Peng, Ying, Mou, Kai, Zhan, Yan, Wang, Yi-Min, Ji, Wei, Xu, Chun, Xiao, Le-Dong, Chen, Yan, Wang, Hua, She, Zhi-Hua, Dai, Peng, Zhao, Gan-Ye, Wang, Yang, Yu, Lu-Lu, Yu, Miao, Liu, Ke, Cui, Jia-Jia, Liu, Rong, Li, Xi, Huang, Yuan-Fei, Liu, Zhao-Qian, Ouyang, Dong-Sheng, Zhang, Wei, Li, Qing, Xiong, Xing-Liang, Guo, Cheng-Xian, Li, Jin-Gao, Lv, Qiao-Li, Xing, Qing-He, Wang, Hai-Jian, Li, Zhi-Ling, Wu, Ji-Chu, Huang, Long-Jian, He, Jian, Tan, Li-Ming, Hong, Wen-Xu, Wang, Xue-Chang, Li, Chao-Peng, Lu, Qin, Zhang, Long, Kong, Xiang-Dong, Zhou, Hong-Hao, and Yin, Ji-Ye

Published
2025
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37. Distributed Disturbance Observer-Based Containment Control of Multi-Agent Systems with Event-Triggered Communications

Author

Lin Hu and Long Jian

Subjects
multi-agent systems, event-triggered control, disturbance observer, containment control, Mathematics, QA1-939
Abstract

This article investigates a class of multi-agent systems (MASs) with known dynamics external disturbances, where the communication graph is directed, and the followers have undirected connections. To eliminate the impacts of external disturbance, the technologies of disturbance observer-based control are introduced into the containment control problems. Additionally, to save communication costs and energy consumption, a distributed disturbance observer-based event-triggered controller is employed to achieve containment control and reject disturbance. Furthermore, designing the event-triggered function using an exponential function is beneficial for a time-dependent term while ensuring the exclusion of Zeno behavior. Finally, a numerical simulation is provided to validate the effectiveness of the theoretical analysis.

Published
2024
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43. Design and Research on Coupling Mechanism of Inductive Power Transmission

Author

Liu, Wei, Sun, Liangshun, Su, Mingwei, Wang, Fangrui, Long, Jian, Xiang, Enxin, Bai, Longlei, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Ma, Chengbin, editor, Zhang, Yiming, editor, Li, Siqi, editor, Zhao, Lei, editor, Liu, Ming, editor, and Zhang, Pengcheng, editor

Published
2023
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