1,720,975 research outputs found
The Significance of Porches in Urban Applications: A Method for Automated Modeling and Integration
Full text linkPorches, as defined by the Art & Architecture Thesaurus, serve as vital transitional spaces linking indoor and outdoor environments. Despite their historical and contemporary significance, porches lack explicit representation in prevalent standards like CityGML and IndoorGML, posing challenges for comprehensive spatial modeling and its application. This paper proposes a method for modeling porches that aligns with the existing OGC standard CityGML 3.0, ensuring accuracy and compatibility. Drawing upon geomatics techniques, the method aims to bridge the gap in representing these spaces, critical for applications such as navigation systems, urban planning, and energy simulations. By integrating geometric, machine learning, and informative modeling approaches, this method seeks to provide a robust foundation for various practical applications. The paper outlines a comprehensive state-of-the-art review, describes the proposed method from digitalization to random forest (RF)-based point cloud classification and vectorization, presents case studies and results, and offers critical discussions and conclusions. Through this endeavor, the paper contributes to enhancing the representation and understanding of porches within the digital spatial landscape
A Comprehensive Understanding of Machine Learning and Deep Learning Methods for 3D Architectural Cultural Heritage Point Cloud Semantic Segmentation
No full textAs a result of the development of Artificial Intelligence (AI) techniques, in recent years, machine learning (ML) and deep learning (DL) approaches have been widely used to semantically enrich 3D architectural cultural heritage (ACH) point clouds. While existing approaches for analyzing and interpreting point clouds continue to improve, the generalizability of pre-trained ML and DL methods to various types of historic buildings remains uncertain. In this context, a comprehensive understanding of both methodologies can enable us to make more effective use of AI techniques in the ACH domain (e.g., data exploitation, model definition, analysis, and preservation). This work presents and compares two very different approaches for the 3D ACH semantic segmentation task. Specifically, we train and test a ML method based on the Random Forest (RF) classifier on the point cloud of three chapels part of the “Sacromonte Calvario di Domodossola” and on the two test scenes of the ArCH dataset. Then, we employ dynamic graph convolutional neural network (DGCNN) as our DL method, training on the ArCH dataset and testing on both the two unseen test scenes of the ArCH dataset and on the “Sacrimonti” chapel point clouds. We provide empirical experiments to illustrate the efficiency of applying ML and DL methodologies to ACH point clouds. Following that, the advantages and limitations of these two approaches are evaluated through a systematic study of the classification results. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG
UNDERSTANDING 3D POINT CLOUD DEEP NEURAL NETWORKS BY VISUALIZATION TECHNIQUES
No full textIn the wake of the success of Deep Learning Networks (DLN) for image recognition, object detection, shape classification and semantic segmentation, this approach has proven to be both a major breakthrough and an excellent tool in point cloud classification. However, understanding how different types of DLN achieve still lacks. In several studies the output of segmentation/classification process is compared against benchmarks, but the network is treated as a "black-box" and intermediate steps are not deeply analysed. Specifically, here the following questions are discussed: (1) what exactly did DLN learn from a point cloud? (2) On the basis of what information do DLN make decisions? To conduct such a quantitative investigation of these DLN applied to point clouds, this paper investigates the visual interpretability for the decision-making process. Firstly, we introduce a reconstruction network able to reconstruct and visualise the learned features, in order to face with question (1). Then, we propose 3DCAM to indicate the discriminative point cloud regions used by these networks to identify that category, thus dealing with question (2). Through answering the above two questions, the paper would like to offer some initial solutions to better understand the application of DLN to point clouds
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
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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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