Related papers: Machine Learning for Semi-Automated Meteorite Reco…
Over the past decade the use of machine learning in meteorology has grown rapidly. Specifically neural networks and deep learning have been used at an unprecedented rate. In order to fill the dearth of resources covering neural networks…
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…
Despite ablation and drag processes associated with atmospheric entry of meteoroids were a subject of intensive study over the last century, little attention was devoted to interpret the observed fireball terminal height. This is a key…
Iron meteorite falls are rare compared to stony meteorites, and until recently no iron meteorite had a reliably determined pre-atmospheric orbit. This changed on 2020 November 7, when a bright fireball was observed across Sweden and…
On Aug 22, 2016, a bright fireball was observed by the Desert Fireball Network in South Australia. Its pre-atmosphere orbit suggests it was temporarily captured by the Earth-Moon system before impact. A search was conducted two years after…
Understanding dynamic 3D environment is crucial for robotic agents and many other applications. We propose a novel neural network architecture called $MeteorNet$ for learning representations for dynamic 3D point cloud sequences. Different…
In recent years, increased wildfires have caused irreversible damage to forest resources worldwide, threatening wildlives and human living conditions. The lack of accurate frontline information in real-time can pose great risks to…
Recently, the use of machine learning in meteorology has increased greatly. While many machine learning methods are not new, university classes on machine learning are largely unavailable to meteorology students and are not required to…
Machine learning has been effective at detecting patterns and predicting the response of systems that behave free of natural laws. Examples include learning crowd dynamics, recommender systems and autonomous mobility. There also have been…
Machine Learning algorithms are good tools for both classification and prediction purposes. These algorithms can further be used for scientific discoveries from the enormous data being collected in our era. We present ways of discovering…
Estimating the meteoroid flux density at centimetre to metre sizes is notoriously difficult. Yet it is an important endeavour, as these sizes represent the transition between small meteoroids that pose a risk to spacecraft, and the…
Remote magnetic sensing can be used to monitor the position of objects in real-time, enabling ground transport monitoring, underground infrastructure mapping and hazardous detection. However, magnetic signals are typically weak and complex,…
Current post-processing techniques for the correction of atmospheric seeing in solar observations -- such as Speckle interferometry and Phase Diversity methods -- have limitations when it comes to their reconstructive capabilities of solar…
Meteors are important phenomenon reflecting many properties of interplanetary dust particles. The study of their origin, mass distribution, and orbit evolution all require large data volume, which can only be obtained using large meteor…
On the 27th of November 2015, at 10:43:45.526 UTC, a fireball was observed across South Australia by ten Desert Fireball Network observatories lasting 6.1 s. A $\sim37$ kg meteoroid entered the atmosphere with a speed of…
Context. Generating a synthetic dataset of meteoroid orbits is a crucial step in analysing the probabilities of random grouping of meteoroid orbits in automated meteor shower surveys. Recent works have shown the importance of choosing a low…
Landslides are destructive and recurrent natural disasters on steep slopes and represent a risk to lives and properties. Knowledge of relict landslides location is vital to understand their mechanisms, update inventory maps and improve risk…
We present a data-driven and physics-informed algorithm for drilling accident forecasting. The core machine-learning algorithm uses the data from the drilling telemetry representing the time-series. We have developed a Bag-of-features…
Rock bolts are crucial components of the subterranean support systems in underground mines that provide adequate structural reinforcement to the rock mass to prevent unforeseen hazards like rockfalls. This makes frequent assessments of such…
Every moment, countless meteoroids enter our atmosphere unseen. The detection and measurement of meteors offer the unique opportunity to gain insights into the composition of our solar systems' celestial bodies. Researchers, therefore,…