Optical microscopy is an essential tool for biologists, who are often faced with the need to overcome the spatial and temporal resolution limitations of their devices to capture finer details. As upgrading imaging hardware is expensive, computational metho ...
This study presents a novel framework for evaluating the luminance measurement capabilities of High Dynamic Range (HDR) sensor cameras in indoor glare conditions. Results indicate that the practical usage range of the CSEM VIP camera is significantly lower ...
Artificial Neural Networks (ANN) are habitually trained via the back-propagation (BP) algorithm. This approach has been extremely successful: Current models like GPT-3 have O(10 11 ) parameters, are trained on O(10 11 ) words and produce awe-inspiring resu ...
Vision systems built around conventional image sensors have to read, encode and transmit large quantities of pixel information, a majority of which is redundant. As a result, new computational imaging sensor architectures were developed to preprocess the r ...
In recent years, new emerging immersive imaging modalities, e.g. light fields, have been receiving growing attention, becoming increasingly widespread over the years. Light fields are often captured through multi-camera arrays or plenoptic cameras, with th ...
This thesis focuses on two selected learning problems: 1) statistical inference on graphs models, and, 2) gradient descent on neural networks, with the common objective of defining and analysing the measures that characterize the fundamental limits.In th ...
This paper develops high-order accurate entropy stable (ES) adaptive moving mesh finite difference schemes for the two- and three-dimensional special relativistic hydrodynamic (RHD) and magnetohydrodynamic (RMHD) equations, which is the high-order accurate ...
A force-feedback surface that creates and modulates distinctive profile and stiffnessto interact with a user in contact thereto, the surface being functionally independentto be used as a single module but can be customized to extend the application indiver ...
This paper extends the high-order entropy stable (ES) adaptive moving mesh finite difference schemes developed in Duan and Tang (2022) to the two- and three-dimensional (multi-component) compressible Euler equations with the stiffened equation of state (EO ...
Recent developments in network neuroscience have highlighted the importance of developing techniques for analysing and modelling brain networks. A particularly powerful approach for studying complex neural systems is to formulate generative models that use ...
