Deep learning-based algorithms can provide state-of-the-art accuracy for remote sensing
technologies such as unmanned aerial vehicles (UAVs)/drones, potentially enhancing their …

Abstract UnmannedAerial Vehicles (UAVs), equipped with camera sensors can facilitate
enhanced situational awareness for many emergency response and disaster management …

Usage of Unmanned Aerial Vehicles (UAVs) is growing rapidly in a wide range of consumer
applications, as they prove to be both autonomous and flexible in a variety of environments …

Accurate and timely access to data describing disaster impact and extent of damage is key
to successful disaster management (a process that includes prevention, mitigation …

Abstract Deep Neural Networks (DNNs) learn representation from data with an impressive
capability, and brought important breakthroughs for processing images, time-series, natural …

Floods are one of the most fatal and devastating disasters, instigating an immense loss of
human lives and damage to property, infrastructure, and agricultural lands. To cater to this …

There are numerous applications of unmanned aerial vehicles (UAVs) in the management of
civil infrastructure assets. A few examples include routine bridge inspections, disaster …

Deep learning is recently showing outstanding results for solving a wide variety of robotic
tasks in the areas of perception, planning, localization, and control. Its excellent capabilities …

Forest fires are caused naturally by lightning, high atmospheric temperatures, and dryness.
Forest fires have ramifications for both climatic conditions and anthropogenic ecosystems …

The automatic detection of aircrafts from SAR images is widely applied in both military and
civil fields, but there are still considerable challenges. To address the high variety of aircraft …