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Type-1 and Interval Type-2 (IT2) Fuzzy Logic Systems (FLS) excel in handling uncertainty alongside their parsimonious rule-based structure. Yet, in learning large-scale data challenges arise, such as the curse of dimensionality and training…
One of the problems of producing instruments for Extremely Large Telescopes is that their size (and hence cost) scales rapidly with telescope aperture. To try to break this relation alternative new technologies have been proposed, such as…
IRIS (InfraRed Imaging Spectrograph) is the diffraction-limited first light instrument for the Thirty Meter Telescope (TMT) that consists of a near-infrared (0.84 to 2.4 $\mu$m) imager and integral field spectrograph (IFS). The IFS makes…
Full Waveform Inversion (FWI) reconstructs high-resolution subsurface models via multi-variate optimization but faces challenges with solver selection and data availability. Deep Learning (DL) offers a promising alternative, bridging…
Over nearly two decades, Differential Dynamic Microscopy (DDM) has become a standard technique for extracting dynamic correlation functions from time-lapse microscopy data, with applications spanning colloidal suspensions, polymer…
The problem of unsupervised learning and segmentation of hyperspectral images is a significant challenge in remote sensing. The high dimensionality of hyperspectral data, presence of substantial noise, and overlap of classes all contribute…
Scientific applications are often irregular and characterized by large computationally-intensive parallel loops. Dynamic loop scheduling (DLS) techniques improve the performance of computationally-intensive scientific applications via load…
The upcoming generation of telescopes, instruments, and surveys is poised to usher in an unprecedented "Big Data" era in the field of astronomy. Within this context, even seemingly modest tasks such as spectral line analyses could become…
The LOw Frequency ARray (LOFAR) is a next-generation radio telescope which uses thousands of stationary dipoles to observe celestial phenomena. These dipoles are grouped in various 'stations' which are centred on the Netherlands with…
Analyses of IFU data are typically performed on a per-spaxel basis, with each spectrum modelled independently. For low signal-to-noise (S/N) features such as weak emission lines, estimating properties is difficult and imprecise. Arbitrary…
Medical image segmentation has achieved remarkable success through the continuous advancement of UNet-based and Transformer-based foundation backbones. However, clinical diagnosis in the real world often requires integrating domain…
This paper introduces a 3D point cloud sequence learning model based on inconsistent spatio-temporal propagation for LiDAR odometry, termed DSLO. It consists of a pyramid structure with a spatial information reuse strategy, a sequential…
One of the most important techniques for astrophysics with adaptive optics is the ability to do spectroscopy at diffraction limited scales. The extreme difficulty of positioning a faint target accurately on a very narrow slit can be avoided…
Non-circuit theory drift-diffusion numerical simulation of standard potentiostatic impedance spectroscopy (IS) is a well-known strategy for characterization of materials and electronic devices. It implies the time-dependent solutions from…
Convolutional neural networks are widely used in various segmentation tasks in medical images. However, they are challenged to learn global features adaptively due to the inherent locality of convolutional operations. In contrast, MLP…
Coherent photonic computing uses both the phase and amplitude of light to implement linear operations such as dot products and matrix multiplication but requires phase stability between the interfering paths. This poses a challenge for such…
Plane wave imaging (PWI) in medical ultrasound is becoming an important reconstruction method with high frame rates and new clinical applications. Recently, single PWI based on deep learning (DL) has been studied to overcome lowered frame…
In fluid flow imaging, intensity gradients are a good measure of spatial variations in scalar properties, which play an important role in controlling transport processes. However, current flow imaging techniques exhibit system-limited…
We have undertaken a major enhancement of our IDL-based simulation tools developed earlier for modeling microwave and X-ray emission. The object-based architecture provides an interactive graphical user interface that allows the user to…
Deformable image registration (DIR) is a crucial and challenging technique for aligning anatomical structures in medical images and is widely applied in diverse clinical applications. However, existing approaches often struggle to capture…