Earthquake Disaster Assessment (EDA) plays a critical role in earthquake disaster
prevention, evacuation, and rescue efforts. Deep learning (DL), which boasts advantages in …

Currently, the most advanced high-resolution remote sensing image (HRRSI) semantic
labeling methods rely on deep neural networks. However, HRRSIs naturally have a serious …

The complexity of the biogeochemical cycle of phosphorus in lakes makes it challenging to
produce efficient and accurate predictions of total phosphorus (TP) concentrations. In this …

Disaster classification and victim detection are two important tasks in enabling efficient
rescue operations. In this paper, we propose a multi-task learning (MTL) model which …

This article surveys the growing interest in utilizing Deep Learning (DL) as a powerful tool to
address challenging problems in earthquake engineering. Despite decades of advancement …

Natural catastrophes may strike anywhere at any moment and cause widespread
destruction. Most people do not have the necessary catastrophe preparedness knowledge …

In this paper, a point cloud extraction method based on the template grid was proposed for
deformation analysis. Firstly, coordinate alignment was carried out by a coarse-to-fine …

针对无人机领域中的监管问题, 基于YOLOv5-Lite 的改进模型, 提出了一种随着训练过程为模型
动态地分配损失权重的指数移动样本加权函数. 通过模型运算, 控制二自由度云台对无人机实时 …

This chapter explores the transformative integration of GPUs and AI accelerators in natural
disaster management, ushering in resilience and rapid response. From early warning …

Sažetak Catastrophic occurrences induced by disasters often lead to fatalities, extensive
damage, and societal disruptions. In pursuit of realizing disaster-resilient smart cities, video …