1,720,962 research outputs found
Apprendre et utiliser des représentations Lidar exploitables sans annotations
No full textThe development of autonomous driving systems heavily relies on accurate perception algorithms trained on large annotated datasets. However, collecting and annotating Lidar point cloud data is particularly expensive and time-consuming, creating a significant bottleneck for scaling autonomous driving technologies, and adapting it to new systems and environments. This thesis addresses this challenge by developing methods to reduce the reliance on annotated Lidar data through self-supervised and unsupervised learning approaches.We present four main contributions that progressively tackle different aspects of this annotation burden.First, we introduce, a method to transfer knowledge from pre-trained natural image models to Lidar networks through image-to-Lidar self-supervised distillation. This approach leverages the abundance of natural images and their corresponding self-supervised representations to train Lidar perception models without requiring Lidar-specific annotations.Second, we propose a purely contrastive self-supervised method for Lidar point clouds that operates in Bird's Eye View space. Unlike image-to-Lidar approaches, it preserves Lidar-specific information such as precise 3D localization while leveraging temporal consistency to learn meaningful representations for semantic segmentation and object detection tasks.Third, we develop a method, which exploits the natural separability of objects in 3D space to perform instance segmentation without any supervision. We demonstrate that temporal consistency and geometric properties of point clouds can be leveraged to create instance pseudo-labels, enabling online instance segmentation of objects through time.Finally, we prove that state-of-the-art Lidar panoptic segmentation can be achieved using only semantic annotations, eliminating the need for instance-level labels. This work reveals that semantic predictions are the primary limiting factor in panoptic segmentation, while instance separation can be effectively solved through clustering approaches.Our contributions collectively show that significant progress can be made in Lidar perception tasks while dramatically reducing annotation requirements. The methods developed in this thesis have practical implications for autonomous driving systems, enabling more cost-effective development and deployment while maintaining high performance standards.Le développement de systèmes de conduite autonome repose largement sur des algorithmes de perception précis entraînés sur de grands ensembles de données annotées. Cependant, la collecte et l'annotation de données de nuages de points Lidar sont particulièrement coûteuses et chronophages, limitant significativement le passage à l'échelle des technologies de conduite autonome. Cette thèse aborde ce défi en développant des méthodes pour réduire la dépendance aux données Lidar annotées grâce à des approches d'apprentissage auto-supervisé et non supervisé.Nous présentons quatre contributions principales qui s'attaquent progressivement à différents aspects de ces coûts d'annotation.Premièrement, nous introduisons une méthode pour transférer les connaissances de modèles d'images pré-entraînés par auto-supervision vers des réseaux Lidar par une distillation de l'image vers le Lidar. Cette approche exploite l'abondance d'images naturelles et leurs représentations auto-supervisées correspondantes pour entraîner des modèles de perception Lidar sans nécessiter d'annotations spécifiques.Deuxièmement, nous proposons une méthode purement contrastive auto-supervisée pour les nuages de points Lidar qui opère dans le plan horizontal ou "Bird's Eye View". Contrairement aux approches image-vers-Lidar, cette approche préserve les informations spécifiques au Lidar telles que la localisation 3D précise tout en exploitant la cohérence temporelle pour apprendre des représentations significatives pour les tâches de segmentation sémantique et de détection d'objets.Troisièmement, nous développons une méthode qui exploite la séparabilité naturelle des objets dans l'espace 3D pour effectuer une segmentation d'instance sans aucune supervision. Nous démontrons ainsi que la cohérence temporelle et les propriétés géométriques des nuages de points peuvent être exploitées pour créer des pseudo-annotations d'instances, permettant une segmentation séquentielle des objets au cours du temps.Enfin, nous prouvons que la segmentation panoptique Lidar peut être réalisée à un niveau de performance similaire aux meilleurs réseaux appris actuels, en utilisant uniquement des annotations sémantiques, sans nécessiter d'annotations d'instances. Ce travail révèle que les prédictions sémantiques sont le facteur limitant principal dans la segmentation panoptique, tandis que la séparation d'instance peut être efficacement résolue par des approches de clustering.Nos contributions montrent collectivement que des progrès significatifs peuvent être réalisés dans les tâches de perception Lidar tout en réduisant drastiquement le besoin d'annotations humaines. Les méthodes développées dans cette thèse ont des implications pratiques pour les systèmes de conduite autonome, permettant un développement et un déploiement moins coûteux tout en maintenant des standards de performance élevés
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
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
Author Under Sail The Imagination of Jack London, 1893-1902
No full textIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Intro -- Title Page -- Copyright Page -- Dedication -- Contents -- Acknowledgments -- Introduction -- 1. Spirit Truth -- 2. From Absorption to Theatricality and Back Again -- 3. "I Will Build a New Present" -- 4. Sons as Authors -- 5. Fathers as Publishers -- 6. The Daughter as Author -- 7. Lovers as Authors -- 8. At Sea with the Family -- 9. Yellow News, Yellow Stories -- 10. The Return Home -- Notes -- Bibliography -- Index -- About Jay WilliamsIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Description based on publisher supplied metadata and other sources.Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, YYYY. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
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