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Few-shot learning problem focuses on recognizing unseen classes given a few labeled images. In recent effort, more attention is paid to fine-grained feature embedding, ignoring the relationship among different distance metrics. In this…

Multimodal aerial data are used to monitor natural systems, and machine learning can significantly accelerate the classification of landscape features within such imagery to benefit ecology and conservation. It remains under-explored,…

This paper discusses the multi-wavelength scanning Raman lidar being built at Lidar Division, CEILAP (CITEDEF-CONICET) in the frame of the Argentinean Cherenkov Telescope Array (CTA) collaboration to measure the spectral characteristics of…

Landmines remain a persistent humanitarian threat, with an estimated 110 million mines deployed across 60 countries, claiming approximately 26,000 casualties annually. Current detection methods are hazardous, inefficient, and prohibitively…

Toward the goal of using Scientific Machine Learning (SciML) emulators to improve the numerical representation of aerosol processes in global atmospheric models, we explore the emulation of aerosol microphysics processes under cloud-free…

Precipitable water vapor (PWV) is an important climate parameter indicative of available moisture in the atmosphere, it is also an important greenhouse gas. Observations of precipitable water vapor in sub-Sahel West Africa are almost…

We present data driven deep learning models for forecasting and monitoring amine emissions and key performance parameters in amine-based post-combustion carbon capture systems. Using operational data from the CESAR1 solvent campaign at…

Multimodal Image Fusion (MMIF) integrates complementary information from various modalities to produce clearer and more informative fused images. MMIF under adverse weather is particularly crucial in autonomous driving and UAV monitoring…

AMANDA is a high-energy neutrino telescope presently under construction at the geographical South Pole. In the Antarctic summer 1995/96, an array of 80 optical modules (OMs) arranged on 4 strings (AMANDA-B4) was deployed at depths between…

Significant efforts have been directed towards adapting self-supervised multimodal learning for Earth observation applications. However, most current methods produce coarse patch-sized embeddings, limiting their effectiveness and…

Millimeter wave (mmWave) radars have attracted significant attention from both academia and industry due to their capability to operate in extreme weather conditions. However, they face challenges in terms of sparsity and noise…

This work analyzes the performance of a downlink multi-user multiple-input multiple-output (MU-MIMO) non-orthogonal multiple access (NOMA) communications system. To reduce hardware complexity and exploit antenna diversity, we consider a…

Accurate and timely regional weather prediction is vital for sectors dependent on weather-related decisions. Traditional prediction methods, based on atmospheric equations, often struggle with coarse temporal resolutions and inaccuracies.…

With the global refugee crisis at a historic high, there is a growing need to assess the impact of refugee settlements on their hosting countries and surrounding environments. Because fires are an important land management practice in…

Seasonal climate forecasts are commonly based on model runs from fully coupled forecasting systems that use Earth system models to represent interactions between the atmosphere, ocean, land and other Earth-system components. Recently,…

Visually poor scenarios are one of the main sources of failure in visual localization systems in outdoor environments. To address this challenge, we present MOZARD, a multi-modal localization system for urban outdoor environments using…

Visible-Infrared Person Re-Identification (VI-ReID) plays a crucial role in applications such as search and rescue, infrastructure protection, and nighttime surveillance. However, it faces significant challenges due to modality…

The main goal of this work is the analysis of new approaches to the study of the properties of astronomical sites. In particular, satellite data measuring aerosols have recently been proposed as a useful technique for site characterization…

Experiments were performed with prototype antenna tiles for the Mileura Widefield Array--Low Frequency Demonstrator (MWA-LFD) to better understand the widefield, wideband properties of their design and to characterize the radio frequency…

This paper presents a unique outdoor aerial visual-inertial-LiDAR dataset captured using a multi-sensor payload to promote the global navigation satellite system (GNSS)-denied navigation research. The dataset features flight distances…