Keywords
Abstract
Urban monitoring systems must process visual evidence under rain, poor lighting, and sensor heterogeneity. Continual de-raining methods support reliable image restoration, while domain adaptation improves segmentation performance under rainy conditions. Infrared-visible image fusion and LiDAR-guided hyperspectral cross-attention provide complementary multimodal approaches for target-aware sensing and image classification. These visual methods are relevant to flood-prone cities where monitoring infrastructure supports adaptation planning and emergency response. Decentralized governance research adds a social dimension by examining political motives, organizational conflicts, and social capital in Web3 communities. LLM confidence research also supports careful interpretation of automated outputs when visual AI is used in policy contexts. This literature cluster connects weather-robust computer vision, multimodal remote sensing, decentralized governance, and flood adaptation.
References
Zhou, Y. (2022). Pre-disaster relocation and agent-based model for flood disaster. The University of Wisconsin-Madison.
Dai, Y. (2026). Rescaling confidence: What scale design reveals about LLM metacognition. arXiv preprint arXiv:2603.09309.
Yang, T., Pan, H., Hewings, G., & Jin, Y. (2019). Understanding urban sub-centers with heterogeneity in agglomeration economies—Where do emerging commercial establishments locate?. Cities, 86, 25-36.
Liu, M., Yang, W., & Liu, J. (2026). Prompting Rain Off: Evolving Compact Dual Prompts for Continual De-Raining. IEEE Transactions on Image Processing.
Liu, M., Xie, J., Hu, Y., Yang, W., & Liu, J. (2023, July). Comprehensive Augmented Domain Adaptation for Image Segmentation Under Rainy Conditions. In 2023 IEEE International Conference on Multimedia and Expo Workshops (ICMEW) (pp. 63-68). IEEE.
Liu, M., Yang, W., Hu, Y., & Liu, J. (2023, August). Dual prompt learning for continual rain removal from single images. In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (Vol. 3).
Sun, T., Xiang, D., Ding, T., Fang, X., Qi, Y., & Zhao, Z. (2025, September). Modality-aware infrared and visible image fusion with target-aware supervision. In 2025 6th International Conference on Computer Vision and Data Mining (ICCVDM) (pp. 180-184). IEEE.
Chen, H., Duan, X., El Saddik, A., & Cai, W. (2025, May). Political Leanings in Web3 Betting: Decoding the Interplay of Political and Profitable Motives. In Proceedings of the 17th ACM Web Science Conference 2025 (pp. 96-105).
Chen, H., & Cai, W. (2023). A comparative analysis of centralized and decentralized developer autonomous organizations managing conflicts in discussing external crises. IEEE Transactions on Computational Social Systems, 11(6), 8118-8129.
Chen, H., Zhou, C., El Saddik, A., & Cai, W. (2025). Decentralized Web3 non-fungible token community for societal prosperity? A social capital perspective. Proceedings of the ACM on Human-Computer Interaction, 9(2), 1-36.
Yang, J. X., Zhou, J., Wang, J., Tian, H., & Liew, A. W. C. (2024). LiDAR-guided cross-attention fusion for hyperspectral band selection and image classification. IEEE Transactions on Geoscience and Remote Sensing, 62, 1-15.