1,720,969 research outputs found
Extraction of characteristics on images acquired in a mobile context : Application to the recognition of defects on civil engineering structures
No full textLe réseau ferroviaire français dispose d’une infrastructure de grande ampleur qui se compose de nombreux ouvrages d’art. Ces derniers subissent les dégradations du temps et du trafic et font donc l’objet d’une surveillance périodique pour détecter l’apparition de défauts. Aujourd’hui, cette inspection se fait en grande partie, visuellement par des opérateurs experts. Plusieurs entreprises testent de nouveaux vecteurs d’acquisition photo comme le drone, destinés à la surveillance des ouvrages de génie civil. Dans cette thèse, l’objectif principal est de développer un système capable de détecter, localiser et enregistrer d’éventuels défauts de l’ouvrage. Un grand défi est de détecter des défauts sous-pixels comme les fissures en temps réel pour améliorer l’acquisition. Pour cela, une analyse par seuillage local a été conçue pour traiter de grandes images. Cette analyse permet d’extraire des points d’intérêts (Points FLASH: Fast Local Analysis by threSHolding) où une ligne droite peut se faufiler. La mise en relation intelligente de ces points permet de détecter et localiser les fissures fines. Les résultats de détection de fissures de surfaces altérées issues d'images d'ouvrages d'art démontrent de meilleures performances en temps de calcul et robustesse que les algorithmes existants. En amont de l'étape de détection, il est nécessaire de s’assurer que les images acquises soient de bonne qualité pour réaliser le traitement. Une mauvaise mise au point ou un flou de bougé sont à bannir. Nous avons développé une méthode réutilisant les calculs de la détection en extrayant des mesures de Local Binary Patterns (LBP) afin de vérifier la qualité en temps réel. Enfin, pour réaliser une acquisition permettant une reconstruction photogrammétrique, les images doivent avoir un recouvrement suffisant. Notre algorithme, réutilisant les points d’intérêts de la détection, permet un appariement simple entre deux images sans passer par des algorithmes de type RANSAC. Notre méthode est invariante en rotation, translation et à une certaine plage de changements d’échelle. Après l’acquisition, sur les images de qualité optimale, il est possible d'employer des méthodes plus coûteuses en temps comme les réseaux de neurones à convolution. Ces derniers bien qu'incapables d’assurer une détection de fissures en temps réel peuvent être utilisés pour détecter certains types d’avaries. Cependant, le manque de données impose la constitution de notre propre jeu de données. A l'aide d'approches de classification indépendante (classifieurs SVM one-class), nous avons développé un système flexible capable d’évoluer dans le temps, de détecter puis de classifier les différents types de défauts. Aucun système de ce type n’apparaît dans la littérature. Les travaux réalisés sur l’extraction de caractéristiques sur des images pour la détection de défauts pourront être utiles dans d’autres applications telles que la navigation de véhicules intelligents ou le word-spotting.The french railway network has a huge infrastructure which is composed of many civil engineering structures. These suffer from degradation of time and traffic and they are subject to a periodic monitoring in order to detect appearance of defects. At the moment, this inspection is mainly done visually by monitoring operators. Several companies test new vectors of photo acquisition like the drone, designed for civil engineering monitoring. In this thesis, the main goal is to develop a system able to detect, localize and save potential defects of the infrastructure. A huge issue is to detect sub-pixel defects like cracks in real time for improving the acquisition. For this task, a local analysis by thresholding is designed for treating large images. This analysis can extract some points of interest (FLASH points: Fast Local Analysis by threSHolding) where a straight line can sneak in. The smart spatial relationship of these points allows to detect and localise fine cracks. The results of the crack detection on concrete degraded surfaces coming from images of infrastructure show better performances in time and robustness than the state-of-art algorithms. Before the detection step, we have to ensure the acquired images have a sufficient quality to make the process. A bad focus or a movement blur are prohibited. We developed a method reusing the preceding computations to assess the quality in real time by extracting Local Binary Pattern (LBP) values. Then, in order to make an acquisition for photogrammetric reconstruction, images have to get a sufficient overlapping. Our algorithm, reusing points of interest of the detection, can make a simple matching between two images without using algorithms as type RANSAC. Our method has invariance in rotation, translation and scale range. After the acquisition, with images with optimal quality, it is possible to exploit methods more expensive in time like convolution neural networks. These are not able to detect cracks in real time but can detect other kinds of damages. However, the lack of data requires the constitution of our database. With approaches of independent classification (classifier SVM one-class), we developed a dynamic system able to evolve in time, detect and then classify the different kinds of damages. No system like ours appears in the literature for the defect detection on civil engineering structure. The implemented works on feature extraction on images for damage detection will be used in other applications as smart vehicle navigation or word spotting
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Extraction de caractéristiques sur des images acquises en contexte mobile : Application à la reconnaissance de défauts sur ouvrages d’art
No full textThe french railway network has a huge infrastructure which is composed of many civil engineering structures. These suffer from degradation of time and traffic and they are subject to a periodic monitoring in order to detect appearance of defects. At the moment, this inspection is mainly done visually by monitoring operators. Several companies test new vectors of photo acquisition like the drone, designed for civil engineering monitoring. In this thesis, the main goal is to develop a system able to detect, localize and save potential defects of the infrastructure. A huge issue is to detect sub-pixel defects like cracks in real time for improving the acquisition. For this task, a local analysis by thresholding is designed for treating large images. This analysis can extract some points of interest (FLASH points: Fast Local Analysis by threSHolding) where a straight line can sneak in. The smart spatial relationship of these points allows to detect and localise fine cracks. The results of the crack detection on concrete degraded surfaces coming from images of infrastructure show better performances in time and robustness than the state-of-art algorithms. Before the detection step, we have to ensure the acquired images have a sufficient quality to make the process. A bad focus or a movement blur are prohibited. We developed a method reusing the preceding computations to assess the quality in real time by extracting Local Binary Pattern (LBP) values. Then, in order to make an acquisition for photogrammetric reconstruction, images have to get a sufficient overlapping. Our algorithm, reusing points of interest of the detection, can make a simple matching between two images without using algorithms as type RANSAC. Our method has invariance in rotation, translation and scale range. After the acquisition, with images with optimal quality, it is possible to exploit methods more expensive in time like convolution neural networks. These are not able to detect cracks in real time but can detect other kinds of damages. However, the lack of data requires the constitution of our database. With approaches of independent classification (classifier SVM one-class), we developed a dynamic system able to evolve in time, detect and then classify the different kinds of damages. No system like ours appears in the literature for the defect detection on civil engineering structure. The implemented works on feature extraction on images for damage detection will be used in other applications as smart vehicle navigation or word spotting.Le réseau ferroviaire français dispose d’une infrastructure de grande ampleur qui se compose de nombreux ouvrages d’art. Ces derniers subissent les dégradations du temps et du trafic et font donc l’objet d’une surveillance périodique pour détecter l’apparition de défauts. Aujourd’hui, cette inspection se fait en grande partie, visuellement par des opérateurs experts. Plusieurs entreprises testent de nouveaux vecteurs d’acquisition photo comme le drone, destinés à la surveillance des ouvrages de génie civil. Dans cette thèse, l’objectif principal est de développer un système capable de détecter, localiser et enregistrer d’éventuels défauts de l’ouvrage. Un grand défi est de détecter des défauts sous-pixels comme les fissures en temps réel pour améliorer l’acquisition. Pour cela, une analyse par seuillage local a été conçue pour traiter de grandes images. Cette analyse permet d’extraire des points d’intérêts (Points FLASH: Fast Local Analysis by threSHolding) où une ligne droite peut se faufiler. La mise en relation intelligente de ces points permet de détecter et localiser les fissures fines. Les résultats de détection de fissures de surfaces altérées issues d'images d'ouvrages d'art démontrent de meilleures performances en temps de calcul et robustesse que les algorithmes existants. En amont de l'étape de détection, il est nécessaire de s’assurer que les images acquises soient de bonne qualité pour réaliser le traitement. Une mauvaise mise au point ou un flou de bougé sont à bannir. Nous avons développé une méthode réutilisant les calculs de la détection en extrayant des mesures de Local Binary Patterns (LBP) afin de vérifier la qualité en temps réel. Enfin, pour réaliser une acquisition permettant une reconstruction photogrammétrique, les images doivent avoir un recouvrement suffisant. Notre algorithme, réutilisant les points d’intérêts de la détection, permet un appariement simple entre deux images sans passer par des algorithmes de type RANSAC. Notre méthode est invariante en rotation, translation et à une certaine plage de changements d’échelle. Après l’acquisition, sur les images de qualité optimale, il est possible d'employer des méthodes plus coûteuses en temps comme les réseaux de neurones à convolution. Ces derniers bien qu'incapables d’assurer une détection de fissures en temps réel peuvent être utilisés pour détecter certains types d’avaries. Cependant, le manque de données impose la constitution de notre propre jeu de données. A l'aide d'approches de classification indépendante (classifieurs SVM one-class), nous avons développé un système flexible capable d’évoluer dans le temps, de détecter puis de classifier les différents types de défauts. Aucun système de ce type n’apparaît dans la littérature. Les travaux réalisés sur l’extraction de caractéristiques sur des images pour la détection de défauts pourront être utiles dans d’autres applications telles que la navigation de véhicules intelligents ou le word-spotting
Variations on the Author
Get PDF“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
Get PDFWe 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
Get PDFWe 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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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