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Specialized image processing accelerators are necessary to deliver the performance and energy efficiency required by important applications in computer vision, computational photography, and augmented reality. But creating,…
In this article, we evaluate unsupervised anomaly detection methods in multispectral images obtained with a wavelength-independent synthetic aperture sensing technique, called Airborne Optical Sectioning (AOS). With a focus on search and…
Acquiring data to train deep learning-based object detectors on Unmanned Aerial Vehicles (UAVs) is expensive, time-consuming and may even be prohibited by law in specific environments. On the other hand, synthetic data is fast and cheap to…
The emergence of data-driven computational materials science offers unprecedented opportunities to explore complex material landscapes, complementing experimental research with the discovery of novel compounds. To enable these developments,…
Mahotas is a computer vision library for Python. It contains traditional image processing functionality such as filtering and morphological operations as well as more modern computer vision functions for feature computation, including…
This work proposes the AutoHVSR algorithm that allows for fully-automated processing of horizontal-to-vertical spectral ratio (HVSR) measurements, including those with zero, one, or multiple clear resonances. The AutoHVSR algorithm…
The increasing volumes of astronomical data require practical methods for data exploration, access and visualisation. The Hierarchical Progressive Survey (HiPS) is a HEALPix based scheme that enables a multi-resolution approach to astronomy…
The advancement of machine learning and the availability of large-scale reaction datasets have accelerated the development of data-driven models for computer-aided synthesis planning (CASP) in the past decade. Here, we detail the newest…
We present a technique for creating background-corrected HiPS (Hierarchical Progressive Surveys) from VPHAS+ images using the Montage toolkit. By combining advanced background correction methods and HiPS generation workflows, we produced…
We have designed and implemented a novel way to process wide-field astronomical data within a distributed environment of hardware resources and humanpower. The system is characterized by integration of archiving, calibration, and…
An image preprocessing methodology based on Fourier analysis together with the Laguerre-Gauss Spatial Filter is proposed. This is an alternative to obtain features from aerial images that reduces the feature space significantly, preserving…
Advancements in artificial intelligence (AI) have greatly benefited plant phenotyping and predictive modeling. However, unrealized opportunities exist in leveraging AI advancements in model parameter optimization for parameter fitting in…
Hyperspectral dehazing (HyDHZ) has become a crucial signal processing technology to facilitate the subsequent identification and classification tasks, as the airborne visible/infrared imaging spectrometer (AVIRIS) data portal reports a…
Image processing at scale is a powerful tool for creating new data sets and integrating them with existing data sets and performing analysis and quality assurance investigations. Workflow managers offer advantages in this type of…
Visualizing and navigating through large astronomy images from a remote location with current astronomy display tools can be a frustrating experience in terms of speed and ergonomics, especially on mobile devices. In this paper, we present…
FeynHiggs is a program for computing MSSM Higgs-boson masses and related observables, such as mixing angles, branching ratios, and couplings, including state-of-the-art higher-order contributions. The centerpiece is a Fortran library for…
The methods and techniques for the slitless spectroscopy software aXe, which was designed to reduce data from the various slitless spectroscopy modes of Hubble Space Telescope instruments, are described. aXe can treat slitless spectra from…
The VOXES project's goal is to realize the first prototype of a high resolution and high precision X-ray spectrometer for diffused sources, using Highly Annealed Pyrolitic Graphite (HAPG) crystals combined with precision position detectors.…
Recent advances in deep learning for remote sensing rely heavily on large annotated datasets, yet acquiring high-quality ground truth for geometric, radiometric, and multi-domain tasks remains costly and often infeasible. In particular, the…
The development of an innovative position sensitive pixelated sensor to detect and measure with high precision the coordinates of the ionizing particles is proposed. The silicon avalanche pixel sensors (APiX) is based on the vertical…