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CLIP Multi-modal Hashing for Multimedia Retrieval

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

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

Externí odkaz: http://arxiv.org/abs/2410.07783

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Deep Prompt Multi-task Network for Abuse Language Detection

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

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

Externí odkaz: http://arxiv.org/abs/2403.05268

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Akademický článek

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?

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

Publikováno v: JMIR mHealth and uHealth, Vol 7, Iss 3, p e12573 (2019)

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 u

Externí odkaz: https://doaj.org/article/bd5161dbff96497ca0cc94f0ee9f334a