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Detecting and attributing temperature increases driven by climate change is crucial for understanding global warming and informing adaptation strategies. However, distinguishing human-induced climate signals from natural variability remains…
Capturing images with enough details to solve imaging tasks is a long-standing challenge in imaging, particularly due to the limitations of standard dynamic range (SDR) images which often lose details in underexposed or overexposed regions.…
Cloud and cloud shadow segmentation are fundamental processes in optical remote sensing image analysis. Current methods for cloud/shadow identification in geospatial imagery are not as accurate as they should, especially in the presence of…
Satellites equipped with optical sensors capture high-resolution imagery, providing valuable insights into various environmental phenomena. In recent years, there has been a surge of research focused on addressing some challenges in remote…
This paper presents the development and implementation of a cloud detection algorithm for Proba-V. Accurate and automatic detection of clouds in satellite scenes is a key issue for a wide range of remote sensing applications. With no…
Context: Infrared dark clouds are the coldest and densest portions of giant molecular clouds. The most massive ones represent some of the most likely birthplaces for the next generation of massive stars in the Milky Way. Because a strong…
This work has been accepted by IEEE TGRS for publication. The majority of optical observations acquired via spaceborne earth imagery are affected by clouds. While there is numerous prior work on reconstructing cloud-covered information,…
Cloud detection is a specialized application of image recognition and object detection using remotely sensed data. The task presents a number of challenges, including analyzing images obtained in visible, infrared and multi-spectral…
Clouds classification is a great challenge in meteorological research. The different types of clouds, currently known and present in our skies, can produce radioactive effects that impact on the variation of atmospheric conditions, with the…
Dust emission is an important tool in studies of star-forming clouds, as a tracer of column density and indirectly via the dust evolution that is connected to the history and physical conditions of the clouds. We examine radiative transfer…
In this paper, we introduce Cirrus, a new long-range bi-pattern LiDAR public dataset for autonomous driving tasks such as 3D object detection, critical to highway driving and timely decision making. Our platform is equipped with a…
Cross-spectrum depth estimation aims to provide a depth map in all illumination conditions with a pair of dual-spectrum images. It is valuable for autonomous vehicle applications when the vehicle is equipped with two cameras of different…
Current autonomous driving algorithms heavily rely on the visible spectrum, which is prone to performance degradation in adverse conditions like fog, rain, snow, glare, and high contrast. Although other spectral bands like near-infrared…
Off-road nighttime autonomous driving suffers from unreliable visible-light perception, making infrared modality crucial for accurate freespace detection. However, progress remains limited due to the scarcity of annotated infrared off-road…
Using thermal infrared detectors mounted on drones, and applying techniques from astrophysics, we hope to support the field of conservation ecology by creating an automated pipeline for the detection and identification of certain endangered…
Clouds play a critical role in Earth's hydrological and energy cycles, and accurately representing their properties is essential for effective numerical modeling and weather forecasting. Machine learning methods have been widely used for…
About half of all optical observations collected via spaceborne satellites are affected by haze or clouds. Consequently, cloud coverage affects the remote sensing practitioner's capabilities of a continuous and seamless monitoring of our…
Facial thermography is one of the most popular research areas in infrared thermal imaging, with diverse applications in medical, surveillance, and environmental monitoring. However, in contrast to facial imagery in the visual spectrum, the…
Sun Glare widely exists in the images captured by unmanned ground and aerial vehicles performing in outdoor environments. The existence of such artifacts in images will result in wrong feature extraction and failure of autonomous systems.…
Clouds are a common phenomenon that distorts optical satellite imagery, which poses a challenge for remote sensing. However, in the literature cloudless analysis is often performed where cloudy images are excluded from machine learning…