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Phase retrieval approaches based on DL provide a framework to obtain phase information from an intensity hologram or diffraction pattern in a robust manner and in real time. However, current DL architectures applied to the phase problem…
Human face synthesis and manipulation are increasingly important in entertainment and AI, with a growing demand for highly realistic, identity-preserving images even when only unpaired, unaligned datasets are available. We study unpaired…
Optics-guided thermal UAV image super-resolution has attracted significant research interest due to its potential in all-weather monitoring applications. However, existing methods typically compress optical features to match thermal feature…
Identification of regions affected by floods is a crucial piece of information required for better planning and management of post-disaster relief and rescue efforts. Traditionally, remote sensing images are analysed to identify the extent…
Firefighting is a dynamic activity, in which numerous operations occur simultaneously. Maintaining situational awareness (i.e., knowledge of current conditions and activities at the scene) is critical to the accurate decision-making…
An Unmanned Aerial Vehicle (UAV) is a promising technology for providing wireless coverage to ground user devices. For all the infrastructure communication networks destroyed in disasters, UAVs battery life is challenging during service…
Raw depth images captured in indoor scenarios frequently exhibit extensive missing values due to the inherent limitations of the sensors and environments. For example, transparent materials frequently elude detection by depth sensors;…
Increasing wildfire occurrence has spurred growing interest in wildfire spread prediction. However, even the most complex wildfire models diverge from observed progression during multi-day simulations, motivating need for data assimilation.…
We present a multi-robot system for GPS-denied search and rescue under the forest canopy. Forests are particularly challenging environments for collaborative exploration and mapping, in large part due to the existence of severe perceptual…
The Unmanned Aerial Vehicle (UAV) swarm networks will play a crucial role in the B5G/6G network thanks to its appealing features, such as wide coverage and on-demand deployment. Emergency communication (EC) is essential to promptly inform…
This paper presents a UAV swarm system designed to assist first responders in disaster scenarios like wildfires. By distributing sensors across multiple agents, the system extends flight duration and enhances data availability, reducing the…
Image fusion technology is widely used to fuse the complementary information between multi-source remote sensing images. Inspired by the frontier of deep learning, this paper first proposes a heterogeneous-integrated framework based on a…
Due to their affordable, low mass, and small dimensions, uncooled microbolometer-based thermal focal plane arrays (UC-FPAs) are useful for long-wave infrared (LWIR)imaging applications. However, in outdoor conditions typical in agricultural…
Climate change has intensified the frequency and severity of wildfires, making rapid and accurate prediction of fire spread essential for effective mitigation and response. Physics-based simulators such as FARSITE offer high-fidelity…
This paper presents an adaptive coverage control method for a fleet of off-road and Unmanned Ground Vehicles (UGVs) operating in dynamic (time-varying) agricultural environments. Traditional coverage control approaches often assume static…
Unmanned aerial vehicles (UAVs) are envisioned to complement the 5G communication infrastructure in future smart cities. Hot spots easily appear in road intersections, where effective communication among vehicles is challenging. UAVs may…
Smart cameras are increasingly used in surveillance solutions in public spaces. Contemporary computer vision applications can be used to recognize events that require intervention by emergency services. Smart cameras can be mounted in…
Detecting vehicles in aerial imagery is a critical task with applications in traffic monitoring, urban planning, and defense intelligence. Deep learning methods have provided state-of-the-art (SOTA) results for this application. However, a…
Unmanned aerial vehicles (UAVs) equipped with advanced sensors have opened up new opportunities for monitoring wind power plants, including blades, towers, and other critical components. However, reliable defect detection requires…
Unmanned aerial vehicles (UAVs) equipped with multiple complementary sensors have tremendous potential for fast autonomous or remote-controlled semantic scene analysis, e.g., for disaster examination. In this work, we propose a UAV system…