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Given the current limited knowledge of meteor plasma micro-physics and its interaction with the surrounding atmosphere and ionosphere, meteors are a highly interesting observational target for high-resolution wide-field astronomical…

Digital tracking enables telescopes to detect asteroids several times fainter than conventional techniques. We describe our optimized methodology to acquire, process, and interpret digital tracking observations, and we apply it to probe the…

In unmanned aerial systems, especially in complex environments, accurately detecting tiny objects is crucial. Resizing images is a common strategy to improve detection accuracy, particularly for small objects. However, simply enlarging…

Satellite images are more accessible with the increase of commercial satellites being orbited. These images are used in a wide range of applications including agricultural management, meteorological prediction, damage assessment from…

Soccer ball detection is identified as one of the critical challenges in the RoboCup competition. It requires an efficient vision system capable of handling the task of detection with high precision and recall and providing robust and low…

We present an algorithm developed to measure the fluxes of major meteor showers as observed in NASA's All-Sky Fireball Network cameras. Measurements of fluxes from the All-Sky cameras not only improve the Meteoroid Environment Office's…

In this paper we present a two-step neural network model to separate detections of solar system objects from optical and electronic artifacts in data obtained with the "Asteroid Terrestrial-impact Last Alert System" (ATLAS), a near-Earth…

Object detection in unmanned aerial vehicle (UAV) images remains a highly challenging task, primarily caused by the complexity of background noise and the imbalance of target scales. Traditional methods easily struggle to effectively…

The 500-meter Aperture Spherical Radio Telescope(FAST) has an active reflector. During the observation, the reflector will be deformed into a paraboloid of 300-meters. To improve its surface accuracy, we propose a scheme for photogrammetry…

In recent times, the availability of inexpensive image capturing devices such as smartphones/tablets has led to an exponential increase in the number of images/videos captured. However, sometimes the amateur photographer is hindered by…

Objects gravitationally captured by the Earth-Moon system are commonly called temporarily captured orbiters (TCOs), natural Earth satellites, or minimoons. TCOs are a crucially important subpopulation of near-Earth objects (NEOs) to…

In recent decades, the use of optical detection systems for meteor studies has increased dramatically, resulting in huge amounts of data being analyzed. Automated meteor detection tools are essential for studying the continuous meteoroid…

Accurate determination of fireball direction is essential for retrieving trajectories and velocities. Errors in these measurements have significant implications, affecting the calculated pre-impact orbit, influencing mass estimates, and…

Building footprint extraction from high-resolution aerial images is always an essential part of urban dynamic monitoring, planning and management. It has also been a challenging task in remote sensing research. In recent years, deep neural…

Most of the automatic fire alarm systems detect the fire presence through sensors like thermal, smoke, or flame. One of the new approaches to the problem is the use of images to perform the detection. The image approach is promising since…

Cloud detection in satellite images is an important first-step in many remote sensing applications. This problem is more challenging when only a limited number of spectral bands are available. To address this problem, a deep learning-based…

In differential measurements of the $t\bar{t}b\bar{b}$ process, observables related to the b jets not originating from top quark decays are of special interest to probe the multi-scale QCD nature of the $t\bar{t}b\bar{b}$ process, and the…

We present an application of Deep Learning for the image recognition of asteroid trails in single-exposure photos taken by the Hubble Space Telescope. Using algorithms based on multi-layered deep Convolutional Neural Networks, we report…

Archives of long photometric surveys, like the Kepler database, are a gold mine for studying flares. However, identifying them is a complex task; while in the case of single-target observations it can be easily done manually by visual…

The low resolution of objects of interest in aerial images makes pedestrian detection and action detection extremely challenging tasks. Furthermore, using deep convolutional neural networks to process large images can be demanding in terms…