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Amer, M. R., Siddiquie, B., Khan, S., Divakaran, A., & Sawhney, H. (2014, March). Multimodal fusion using dynamic hybrid models. In IEEE winter conference on applications of computer vision (pp. 556-563). IEEE.Search in Google Scholar
Angelou, M., Solachidis, V., Vretos, N., & Daras, P. (2019). Graph-based multimodal fusion with metric learning for multimodal classification. Pattern Recognition, 95, 296-307.Search in Google Scholar
Luo, Z., Zheng, C., Gong, J., Chen, S., Luo, Y., & Yi, Y. (2023). 3DLIM: Intelligent analysis of students’ learning interest by using multimodal fusion technology. Education and Information Technologies, 28(7), 7975-7995.Search in Google Scholar
Liang, P. P., Cheng, Y., Salakhutdinov, R., & Morency, L. P. (2023, October). Multimodal fusion interactions: A study of human and automatic quantification. In Proceedings of the 25th International Conference on Multimodal Interaction (pp. 425-435).Search in Google Scholar
Poria, S., Cambria, E., Bajpai, R., & Hussain, A. (2017). A review of affective computing: From unimodal analysis to multimodal fusion. Information fusion, 37, 98-125.Search in Google Scholar
Wajid, M. A., & Zafar, A. (2021). Multimodal fusion: a review, taxonomy, open challenges, research roadmap and future directions. Neutrosophic Sets and Systems, 45(1), 8.Search in Google Scholar
Kalamkar, S. (2023). Multimodal image fusion: A systematic review. Decision Analytics Journal, 100327.Search in Google Scholar
Gaonkar, A., Chukkapalli, Y., Raman, P. J., Srikanth, S., & Gurugopinath, S. (2021, June). A comprehensive survey on multimodal data representation and information fusion algorithms. In 2021 International Conference on Intelligent Technologies (CONIT) (pp. 1-8). IEEE.Search in Google Scholar
Zhu, H., Wang, Z., Shi, Y., Hua, Y., Xu, G., & Deng, L. (2020). Multimodal Fusion Method Based on Self‐Attention Mechanism. Wireless Communications and Mobile Computing, 2020(1), 8843186.Search in Google Scholar
Liu, H., Fang, T., Zhou, T., & Wang, L. (2018). Towards robust human-robot collaborative manufacturing: Multimodal fusion. IEEE Access, 6, 74762-74771.Search in Google Scholar
Liu, H., Deng, C., Fernandez-Caballero, A., & Sun, F. (2018). Multimodal fusion for robotics. International Journal of Advanced Robotic Systems, 15(3), 1729881418782832.Search in Google Scholar
Yan, G. (2019). On Geng Lu Jing Circulated Orally among Hainan Fishermen. China Oceans L. Rev., 44.Search in Google Scholar
Dang, T. N. (2012). Fisheries Co-operation in the South China Sea and the (Ir) relevance of the Sovereignty Question. Asian Journal of International Law, 2(1), 59-88.Search in Google Scholar
Liu, L. (2021). The fishermen inhabiting the Xuande and Yongle Islands in Xisha Islands. International Journal of Anthropology and Ethnology, 5(1), 10.Search in Google Scholar
Kurz, J. L. (2019). Gauging the South China Sea: Route Books (genglubu) since 1974. The China Quarterly, 240, 1135-1143.Search in Google Scholar
Zhang, H. (2016). Chinese fishermen in disputed waters: Not quite a “people’s war”. Marine Policy, 68, 65-73.Search in Google Scholar
Roszko, E. (2017). South China Sea: The fishermen on the front lines. The Diplomat, 1.Search in Google Scholar
Zhu, X., Mao, Z., Qu, J., & Zhang, Z. (2024). Historical logic and maritime cultural foundation of China’s initiative of building a maritime community with a shared future. Frontiers in Marine Science, 11, 1362399.Search in Google Scholar
Blussé, L. (2018). Oceanus resartus; or, is Chinese maritime history coming of age?. Cross-Currents: East Asian History and Culture Review, 7(1), 9-29.Search in Google Scholar
Roszko, E. (2021). Navigating seas, markets, and sovereignties: fishers and occupational slippage in the South China Sea. Anthropological Quarterly, 94(4), 639-668.Search in Google Scholar
Amjad A. Alsuwaylimi. (2024). Arabic dialect identification in social media: A hybrid model with transformer models and BiLSTM. Heliyon(17),e36280-e36280.Search in Google Scholar
Bo Yang,Zhaohui Jiang,Dong Pan,Haoyang Yu,Gui Gui & Weihua Gui. (2025). LFDT-Fusion: A latent feature-guided diffusion Transformer model for general image fusion. Information Fusion102639-102639.Search in Google Scholar
Lifeng Han,Serge Gladkoff,Gleb Erofeev,Irina Sorokina,Betty Galiano & Goran Nenadic. (2024). Neural machine translation of clinical text: an empirical investigation into multilingual pre-trained language models and transfer-learning. Frontiers in Digital Health1211564-1211564.Search in Google Scholar