相关论文: FlakeOut: A Geometric Approach to Remove Wind-Blow…

Complex phenomena can be better understood when broken down into a limited number of simpler "components". Linear statistical methods such as the principal component analysis and its variants are widely used across various fields of applied…

In agricultural management, precise Ground Truth (GT) data is crucial for accurate Machine Learning (ML) based crop classification. Yet, issues like crop mislabeling and incorrect land identification are common. We propose a multi-level GT…

In this paper we present two examples of recent investigations that we have undertaken, applying Machine Learning (ML) neural networks (NN) to image datasets from outer planet missions to achieve feature recognition. Our first investigation…

In this paper we present results from the NEFOCAST project, funded by the Tuscany Region, aiming at detecting and estimating rainfall fields from the opportunistic use of the rain-induced excess attenuation incurred in the downlink channel…

In climate science, we often want to compare across different datasets. Difficulties can arise in doing this due to inevitable mismatches that arise between observational and reanalysis data, or even between different reanalyses. This…

We present BLOBCAT, new source extraction software that utilises the flood fill algorithm to detect and catalogue blobs, or islands of pixels representing sources, in two-dimensional astronomical images. The software is designed to process…

We present the first application of a new foreground removal pipeline to the current leading HI intensity mapping dataset, obtained by the Green Bank Telescope (GBT). We study the 15hr and 1hr field data of the GBT observations previously…

Lens flare is a common image artifact that can significantly degrade image quality and affect the performance of computer vision systems due to a strong light source pointing at the camera. This survey provides a comprehensive overview of…

In order to keep track of the operational state of power grid, the world's largest sensor systems, smart grid, was built by deploying hundreds of millions of smart meters. Such system makes it possible to discover and make quick response to…

According to the current standard model of Cosmology, matter in the Universe arranges itself along a network of filamentary structure. These filaments connect the main nodes of this so-called 'Cosmic Web', which are clusters of galaxies.…

A simple Gaussian size deconvolution method is routinely used to remove the blur of observed images caused by insufficient angular resolutions of existing telescopes, thereby to estimate the physical sizes of extracted sources and…

Snow is a highly complex medium composed of ice crystals of various shapes and sizes. Knowledge of its intrinsic optical properties such as the scattering and absorption coefficient is tantamount to radiative transfer models in climate…

In this paper we continue to develop the m-mode formalism, a technique for efficient and optimal analysis of wide-field transit radio telescopes, targeted at 21 cm cosmology. We extend this formalism to give an accurate treatment of the…

Accurate measurements of atmospheric flows at meter-scale resolution are essential for a broad range of sustainability applications, including optimal design of wind and solar farms, safe and efficient urban air mobility, monitoring of…

The ability to subtract foreground contamination from low-frequency observations is crucial to reveal the underlying 21 cm signal. The traditional line-of-sight methods can deal with the removal of diffuse emission and unresolved point…

We investigate the performance of distributed least-mean square (LMS) algorithms for parameter estimation over sensor networks where the regression data of each node are corrupted by white measurement noise. Under this condition, we show…

Smoothing and filtering two-dimensional sequences are fundamental tasks in fields such as computer vision. Conventional filtering algorithms often rely on the selection of the filtering window, limiting their applicability in certain…

Polar mesocyclones (PMCs) and their intense subclass polar lows (PLs) are relatively small atmospheric vortices that form mostly over the ocean in high latitudes. PLs can strongly influence deep ocean water formation since they are…

Machine learning is a useful tool for identifying radio pulses from cosmic-ray air showers and for cleaning such pulses from radio background. This can lower the detection threshold and increase the accuracy for the pulse time and…

Recent advancements in data-driven weather forecasting models have delivered deterministic models that outperform the leading operational forecast systems based on traditional, physics-based models. However, these data-driven models are…