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We demonstrate two new approaches that have been developed to aid the production of future hard X-ray catalogs, and specifically to reduce the reliance on human intervention during the detection of faint excesses in maps that also contain…
Identifying musical instruments in polyphonic music recordings is a challenging but important problem in the field of music information retrieval. It enables music search by instrument, helps recognize musical genres, or can make music…
Artifacts support evaluating new research results and help comparing them with the state of the art in a field of interest. Over the past years, several artifacts have been introduced to support research in the field of self-adaptive…
High dynamic range (HDR) imaging is a technique that allows an extensive dynamic range of exposures, which is important in image processing, computer graphics, and computer vision. In recent years, there has been a significant advancement…
Musical instrument classification, a key area in Music Information Retrieval, has gained considerable interest due to its applications in education, digital music production, and consumer media. Recent advances in machine learning,…
For a long time, RBS and PIXE techniques have been used in the field of cultural heritage. Although the complementarity of both techniques has long been acknowledged, its full potential has not been yet developed due to the lack of general…
X-ray sources are developing rapidly and their coherent output is growing extremely rapidly. The increased coherent flux from modern X-ray sources is being matched with an associated rapid development in experimental methods. This article…
Current and future continuum surveys being undertaken by the new generation of radio telescopes are now poised to address many important science questions, ranging from the earliest galaxies, to the physics of nearby AGN, as well as…
Object detection is one of the most important and challenging branches of computer vision, which has been widely applied in peoples life, such as monitoring security, autonomous driving and so on, with the purpose of locating instances of…
In this paper, we report on our efforts for using Deep Learning for classifying artifacts and their features in digital visuals as a part of the Neoclassica framework. It was conceived to provide scholars with new methods for analyzing and…
Traditional methods to tackle many music information retrieval tasks typically follow a two-step architecture: feature engineering followed by a simple learning algorithm. In these "shallow" architectures, feature engineering and learning…
Diffusion magnetic resonance imaging (dMRI) is a crucial technique in neuroimaging studies, allowing for the non-invasive probing of the underlying structures of brain tissues. Clinical dMRI data is susceptible to various artifacts during…
Quality assessment of diffusion MRI (dMRI) data is essential prior to any analysis, so that appropriate pre-processing can be used to improve data quality and ensure that the presence of MRI artifacts do not affect the results of subsequent…
Engaging in interdisciplinary projects on the intersection between visualization and humanities research can be a challenging endeavor. Challenges can be finding valuable outcomes for both domains, or how to apply state-of-the-art visual…
Understanding the features learned by deep models is important from a model trust perspective, especially as deep systems are deployed in the real world. Most recent approaches for deep feature understanding or model explanation focus on…
This paper describes the methodology currently being implemented in the EIS pipeline for analysing optical/infrared multi-colour data. The aim is to identify different classes of objects as well as possible undesirable features associated…
This paper explores the integration of Artificial Intelligence (AI) in the design of interactive experiences for Cultural Heritage (CH). Previous studies indeed either miss to represent the specificity of the CH or mention possible tools…
In an era where the global population is aging significantly, cognitive impairments among the elderly have become a major health concern. The need for effective assistive technologies is clear, and facial recognition systems are emerging as…
Super-Resolution (SR) has advanced rapidly in recent years, with diffusion-based models achieving unprecedented fidelity at the cost of introducing new types of visual artifacts. While existing Image Quality Assessment (IQA) methods provide…
Face recognition (FR) systems continue to spread in our daily lives with an increasing demand for higher explainability and interpretability of FR systems that are mainly based on deep learning. While bias across demographic groups in FR…