Related papers: $\texttt{raccoon}$: A Python package for removing …
Change detection aims to identify remote sense object changes by analyzing data between bitemporal image pairs. Due to the large temporal and spatial span of data collection in change detection image pairs, there are often a significant…
Radio echo sounding (RES) is a common technique used in subsurface glacial imaging, which provides insight into the underlying rock and ice. However, systematic noise is introduced into the data during collection, complicating…
This paper aims at providing a comprehensive framework to generate an astrophysical scene and to simulate realistic hyperspectral and multispectral data acquired by two JWST instruments, namely NIRCam Imager and NIRSpec IFU. We want to show…
PYROBOCOP is a Python-based package for control, optimization and estimation of robotic systems described by nonlinear Differential Algebraic Equations (DAEs). In particular, the package can handle systems with contacts that are described…
The James Webb Space Telescope produces some of the highest sensitivity imaging of the cosmos across all instruments. One of them, the NIRISS Fine Guidance Sensor, provides guide star imaging with a passband of 0.6 to 5 microns through two…
Ultrasound imaging is crucial for evaluating organ morphology and function, yet depth adjustment can degrade image quality and field-of-view, presenting a depth-dependent dilemma. Traditional interpolation-based zoom-in techniques often…
Synthetic Aperture Radar (SAR) images are often contaminated by a multiplicative noise known as speckle. Speckle makes the processing and interpretation of SAR images difficult. We propose a deep learning-based approach called, Image…
Technical and environmental noise in ground-based laser interferometers designed for gravitational-wave observations like Advanced LIGO, Advanced Virgo and KAGRA, can manifest as narrow (<1Hz) or broadband ($10'$s or even $100'$s of Hz)…
It is challenging to remove rain-steaks from a single rainy image because the rain steaks are spatially varying in the rainy image. This problem is studied in this paper by combining conventional image processing techniques and deep…
We introduce a new regression framework designed to deal with large-scale, complex data that lies around a low-dimensional manifold with noises. Our approach first constructs a graph representation, referred to as the skeleton, to capture…
Sparse-view computed tomography (CT) is a practical solution to reduce radiation dose, but the resulting ill-posed inverse problem poses significant challenges for accurate image reconstruction. Although deep learning and diffusion-based…
Modern radio interferometric arrays offer high sensitivity, wide fields of view, and broad frequency coverage, but also pose significant data calibration challenges. Standard direction-independent calibration is insufficient to correct…
In the clinical setting of histopathology, whole-slide image (WSI) artifacts frequently arise, distorting regions of interest, and having a pernicious impact on WSI analysis. Image-to-image translation networks such as CycleGANs are in…
At least two software packages---DARWIN, Eckerd College, and FinScan, Texas A&M---exist to facilitate the identification of cetaceans---whales, dolphins, porpoises---based upon the naturally occurring features along the edges of their…
This exposition presents nimblewomble, a software package to perform wombling, or boundary analysis, using the nimble Bayesian hierarchical modeling language in the R statistical computing environment. Wombling is used widely to track…
Gravitational waves in the sensitivity band of ground-based detectors can be emitted by a number of astrophysical sources, including not only binary coalescences, but also individual spinning neutron stars. The most promising signals from…
Audio processing methods based on deep neural networks are typically trained at a single sampling frequency (SF). To handle untrained SFs, signal resampling is commonly employed, but it can degrade performance, particularly when the input…
Defective and inconsistent responses in CT detectors can cause ring and streak artifacts in the reconstructed images, making them unusable for clinical purposes. In recent years, several ring artifact reduction solutions have been proposed…
In object detection, the intersection over union (IoU) threshold is frequently used to define positives/negatives. The threshold used to train a detector defines its \textit{quality}. While the commonly used threshold of 0.5 leads to noisy…
\textsc{Pykat} is a Python package which extends the popular optical interferometer modelling software \textsc{Finesse}. It provides a more modern and efficient user interface for conducting complex numerical simulations, as well as…