Image spectroscopy (IS) is an important tool for the noninvasive analysis of works of art. It generates a wide sequence of multispectral images from which a reflectance spectrum for each imaged point can be recovered. In addition, digital processing techniques can be employed to divide the images into areas of similar spectral behavior. An IS system designed and developed in our laboratory is described. The methodology used to process the acquired data integrates spectral analysis with statistical image processing: in particular, the potential of principal-component analysis applied in this area is investigated. A selection of the results obtained from a sixteenth-century oil-painted panel by Luca Signorelli is also reported.
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http://dx.doi.org/10.1364/ao.37.001299 | DOI Listing |
Heliyon
January 2025
Writing Lab, Institute for the Future of Education, Tecnologico de Monterrey, Monterrey, Mexico.
This study analyzes the self-mention forms represented by first-person pronouns (I, me, my, we, us, and our), self-citations, and other forms of mentions made by the same author(s) in each article (e.g., this writer, the author, the authors, the research team) in a corpus of academic articles (625,195 words) in Design area disciplines to determine the similarities and differences in self-mention practices within these disciplines and the previous findings reported in the literature of authorial self-representation observed in hard and soft fields.
View Article and Find Full Text PDFHeliyon
January 2025
BCN MedTech, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.
Deformable image registration is a cornerstone of many medical image analysis applications, particularly in the context of fetal brain magnetic resonance imaging (MRI), where precise registration is essential for studying the rapidly evolving fetal brain during pregnancy and potentially identifying neurodevelopmental abnormalities. While deep learning has become the leading approach for medical image registration, traditional convolutional neural networks (CNNs) often fall short in capturing fine image details due to their bias toward low spatial frequencies. To address this challenge, we introduce a deep learning registration framework comprising multiple cascaded convolutional networks.
View Article and Find Full Text PDFHeliyon
July 2024
College of Information Science and Engineering, Northeastern University, Shenyang 110819, China.
Resting-state functional magnetic resonance imaging (rs-fMRI) is a non-invasive neuroimaging technique widely utilized in the research of Autism Spectrum Disorder (ASD), providing preliminary insights into the potential biological mechanisms underlying ASD. Deep learning techniques have demonstrated significant potential in the analysis of rs-fMRI. However, accurately distinguishing between healthy control group and ASD has been a longstanding challenge.
View Article and Find Full Text PDFThe construction of an admirable hybrid bulk-heterojunction (HBH) can benefit the performance of optoelectronic devices through efficient charge separation and transportation. However, the present HBH structure still suffers from complicated layer-by-layer ligand exchanges during device fabrication. In this work, we apply a liquid phase exchange strategy in mixed colloidal hybrids composed of quantum dots (QDs) and nanotetrapods (NTs) and construct low-cost flexible self-powered infrared photodetectors with a carbon electrode.
View Article and Find Full Text PDFACS Appl Mater Interfaces
January 2025
School of Materials Science and Engineering, Hainan University, Haikou 570228, China.
Biological fouling seriously jeopardizes the development of the marine industry. Although hydrogels, as a kind of state-of-the-art antifouling material, have received wide attention, their mechanical strength is still relatively weak, and the synergistic antifouling method is comparatively single, thus limiting the performance of hydrogels. Here, a zwitterionic sulfobetaine methacrylate (SBMA)-acrylamide (AM)/sodium alginate (SA) double-network (DN) antifouling hydrogel with superb antifouling ability and outstanding mechanical properties was prepared by grafting MXene/Ag (M/Ag) and the powerful biocide polyhexamethylene biguanide (PHMB).
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