With the digitization of modern cities, large data volumes and powerful computational
resources facilitate the rapid update of intelligent models deployed in smart cities. Continual …

Fire detection is a critical safety issue due to the major and irreversible consequences of fire,
from economic prejudices to loss of life. It is therefore of utmost importance to design …

With the exponential growth in the speed and volume of remote sensing data, deep learning
models are expected to adapt and continually learn over time. Unfortunately, the domain …

Reconnaissance unmanned aerial vehicles are specifically designed to estimate
parameters and process intercepted signals for the purpose of identifying and locating …

Wildfires have long been a danger to the atmosphere and ecological environment. With the
advancement of deep learning technology and sensor equipment, wildfire identification …

深度学习的发展推动了高精度遥感图像智能解译模型的涌现. 然而, 目前遥感智能解译模型大多
基于预先定义的静态数据集独立训练, 难以适应环境开放和需求动态的实际应用 …

The early warning of fires is pivotal for preventing substantial economic losses and
ecological damage. However, the enhancement of fire model generalization performance …

It is usually costly or even impossible to obtain required training labels of remote sensing
images for traditional supervised classification method. Domain adaptation approaches can …

Forest fires are characterized by a rapid and devastating nature, underscoring the practical
significance of forest fire risk monitoring. Currently, forest fire risk assessments inadequately …

Recent analyses by leading national wildfire and emergency monitoring agencies have
highlighted an alarming trend: the impact of wildfire devastation has escalated to nearly …