1,720,964 research outputs found
A Tracking System Exploiting Interaction Between a Detector With Localization Capabilities and the KF
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Automated text restoration in ancient manuscripts: a deep learning approach for document image binarisation based on multispectral data
No full textThe development of automatic techniques for the restoration of handwritten texts in ancient, degraded manuscripts is gaining more interest in the field of book heritage. Typically, the task of interpreting the written text is left to expert philologists, who make use of “visible” features (naked eyes or digitization) and contextual information, thus introducing subjectivity into the restoration process. Recent advances in machine learning, especially deep learning, have paved the way for new methods for document analysis that can be integrated into fully automated systems capable of providing objective results. Of particular interest for text restoration are the algorithms related to document image binarisation, which consists in discriminating in the images the text from the background. This paper presents a fully automated processing pipeline for document image binarisation using deep learning based segmentation approaches on digitised images of ancient, degraded manuscripts. To generalize the approach, the method has been tested using image data from different sources, including open datasets and data obtained in laboratory. The experimental datasets were acquired with the PhaseOne multispectral imaging console in the UV-VIS-NIR. The spectral images are first combined to enhance the detection of the manuscript features, by improving the image contrast of the written text with respect to the background. A robust framework for handwritten text segmentation is then applied, enabling an accurate segmentation without the need for manual intervention. The integration of the multispectral data module in the pipeline is investigated in the analysis of the degraded manuscripts that are challenging due to the presence of faded ink and deterioration in the support. Once validated on different type of datasets, the proposed technique may represent a valuable tool for philologists and conservators to save time enabling a scalable analysis of large document collections
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
MADAM: Manuscript Annotated Dataset Based on Multispectral Imaging for Handwritten Text Enhancement and Restoration
No full textBook heritage calls scientists to specific challenges: the object is investigated in its “textual” and “material” features, with the two aspects interlaced, especially in the case of degraded manuscripts. The written text is often not readable directly, but only through the experience of expert philologists who try to recover it using visible traits and contextual information. Considering the recent advances in machine learning, it becomes possible to implement a computer-aided system to help philologists with the above challenging problem. To do that, it is fundamental to get annotated data, allowing the AI algorithms to learn how to recover the degraded information, aiding philologists in their work, but unfortunately, such a kind of dataset is not available yet. To fill this gap, this paper introduces a dataset with high-resolution images of historical Italian manuscripts, in different and severely degraded conditions, acquired through an optimized multispectral imaging setup in the UV-VIS-NIR. For each image patch of the multispectral stack both transcription and segmentation masks of the handwritten text are provided, making the overall built dataset a valuable resource for developing and testing AI algorithms for enhancement, detection, segmentation or restoring text
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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