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Advances in computer AI-assisted multimodal data fusion techniques

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14. Nov. 2024

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Cheng, J., Dai, Y., Yuan, Y., & Zhu, H. (2020, December). A simple analysis of multimodal data fusion. In 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) (pp. 1472-1475). IEEE. Search in Google Scholar

Byeon, H., Raina, V., Sandhu, M., Shabaz, M., Keshta, I., Soni, M., ... & Lakshmi, T. V. (2024). Artificial intelligence-Enabled deep learning model for multimodal biometric fusion. Multimedia Tools and Applications, 1-24. Search in Google Scholar

Knyaz, V. (2019, June). Multimodal data fusion for object recognition. In Multimodal Sensing: Technologies and Applications (Vol. 11059, pp. 198-209). SPIE. Search in Google Scholar

Narkhede, P., Walambe, R., Mandaokar, S., Chandel, P., Kotecha, K., & Ghinea, G. (2021). Gas detection and identification using multimodal artificial intelligence based sensor fusion. Applied System Innovation, 4(1), 3. Search in Google Scholar

John, A., Redmond, S. J., Cardiff, B., & John, D. (2021). A multimodal data fusion technique for heartbeat detection in wearable IoT sensors. IEEE Internet of Things Journal, 9(3), 2071-2082. Search in Google Scholar

Li, J., Hong, D., Gao, L., Yao, J., Zheng, K., Zhang, B., & Chanussot, J. (2022). Deep learning in multimodal remote sensing data fusion: A comprehensive review. International Journal of Applied Earth Observation and Geoinformation, 112, 102926. Search in Google Scholar

Zhao, F., Zhang, C., & Geng, B. (2024). Deep Multimodal Data Fusion. ACM Computing Surveys, 56(9), 1-36. Search in Google Scholar

Chango, W., Lara, J. A., Cerezo, R., & Romero, C. (2022). A review on data fusion in multimodal learning analytics and educational data mining. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 12(4), e1458. Search in Google Scholar

Tang, Q., Liang, J., & Zhu, F. (2023). A comparative review on multi-modal sensors fusion based on deep learning. Signal Processing, 109165. Search in Google Scholar

Jiao, T., Guo, C., Feng, X., Chen, Y., & Song, J. (2024). A Comprehensive Survey on Deep Learning Multi-Modal Fusion: Methods, Technologies and Applications. Computers, Materials & Continua, 80(1). Search in Google Scholar

Farahnakian, F., & Heikkonen, J. (2020). Deep learning based multi-modal fusion architectures for maritime vessel detection. Remote Sensing, 12(16), 2509. Search in Google Scholar

Tang, Z., Xu, T., Wu, X., Zhu, X. F., & Kittler, J. (2024, March). Generative-based fusion mechanism for multi-modal tracking. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 38, No. 6, pp. 5189-5197). Search in Google Scholar

Younis, M. C., & Abuhammad, H. (2021). A hybrid fusion framework to multi-modal bio metric identification. Multimedia Tools and Applications, 80(17), 25799-25822. Search in Google Scholar

Liang, X., Qian, Y., Guo, Q., Cheng, H., & Liang, J. (2021). AF: An association-based fusion method for multi-modal classification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(12), 9236-9254. Search in Google Scholar

Bednarek, M., Kicki, P., & Walas, K. (2020). On robustness of multi-modal fusion—Robotics perspective. Electronics, 9(7), 1152. Search in Google Scholar

Liu, S., Gao, P., Li, Y., Fu, W., & Ding, W. (2023). Multi-modal fusion network with complementarity and importance for emotion recognition. Information Sciences, 619, 679-694. Search in Google Scholar

CHEN, X., XIE, H., TAO, X., WANG, F. L., LENG, M., & LEI, B. (2024). Artificial intelligence and multimodal data fusion for smart healthcare: topic modeling and bibliometrics. Artificial Intelligence Review, 57(4), 91. Search in Google Scholar

Blasch, E. P., Majumder, U., Rovito, T., & Raz, A. K. (2019, July). Artificial intelligence in use by multimodal fusion. In 2019 22th International Conference on Information Fusion (FUSION) (pp. 1-8). IEEE. Search in Google Scholar

Gaw, N., Yousefi, S., & Gahrooei, M. R. (2022). Multimodal data fusion for systems improvement: A review. Handbook of Scholarly Publications from the Air Force Institute of Technology (AFIT), Volume 1, 2000-2020, 101-136. Search in Google Scholar

Restrepo, D., Wu, C., Vásquez-Venegas, C., Nakayama, L. F., Celi, L. A., & López, D. M. (2024). DFDM: A foundational process model for multimodal data fusion in the artificial intelligence era. Research Square. Search in Google Scholar

Zhang, Y. D., Dong, Z., Wang, S. H., Yu, X., Yao, X., Zhou, Q., ... & Gorriz, J. M. (2020). Advances in multimodal data fusion in neuroimaging: overview, challenges, and novel orientation. Information Fusion, 64, 149-187. Search in Google Scholar

Lahat, D., Adali, T., & Jutten, C. (2015). Multimodal data fusion: an overview of methods, challenges, and prospects. Proceedings of the IEEE, 103(9), 1449-1477. Search in Google Scholar

Dai, Y., Yan, Z., Cheng, J., Duan, X., & Wang, G. (2023). Analysis of multimodal data fusion from an information theory perspective. Information Sciences, 623, 164-183. Search in Google Scholar

Munir, A., Blasch, E., Kwon, J., Kong, J., & Aved, A. (2021). Artificial intelligence and data fusion at the edge. IEEE Aerospace and Electronic Systems Magazine, 36(7), 62-78. Search in Google Scholar

Zijun Liu,Li Cai,Wenjie Yang & Junhui Liu. (2024). Sentiment analysis based on text information enhancement and multimodal feature fusion. Pattern Recognition110847-110847. Search in Google Scholar

Wang Shulei. (2023). Res-FLNet: human-robot interaction and collaboration for multi-modal sensing robot autonomous driving tasks based on learning control algorithm. Frontiers in Neurorobotics1269105-1269105. Search in Google Scholar

Jiayu Liang,Yaxin Lu & Mingming Su. (2024). Hga-lstm: LSTM architecture and hyperparameter search by hybrid GA for air pollution prediction. Genetic Programming and Evolvable Machines(2),20-20. Search in Google Scholar

Mokhtari Ichrak,Bechkit Walid,Rivano Herve & Yaici Mouloud Riadh. (2021). Uncertainty-Aware Deep Learning Architectures for Highly Dynamic Air Quality Prediction. IEEE ACCESS14765-14778. Search in Google Scholar

Sprache:
Englisch
Zeitrahmen der Veröffentlichung:
1 Hefte pro Jahr
Fachgebiete der Zeitschrift:
Biologie, Biologie, andere, Mathematik, Angewandte Mathematik, Mathematik, Allgemeines, Physik, Physik, andere