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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
121

Latent semantic web service directory and composition framework a thesis /

Yick, (Winnie) Yuki B. Haungs, Michael L. January 1900 (has links)
Thesis (M.S.)--California Polytechnic State University, 2009. / Mode of access: Internet. Title from PDF title page; viewed on Jan. 6, 2010. Major professor: Dr. Michael Haungs. "Presented to the faculty of California Polytechnic State University, San Luis Obispo." "In partial fulfillment of the requirements for the degree [of] Master of Science in Computer Science." "Aug 2009." Includes bibliographical references (p. 76-78).
122

Improved indexes for next generation bioinformatics applications

Wu, Man-kit, Edward. January 2009 (has links)
Thesis (M. Phil.)--University of Hong Kong, 2010. / Includes bibliographical references (leaves 69-72). Also available in print.
123

Application of the historic preservation index strategy to historic vernacular landscape

Parmar, Sonal D. January 2008 (has links)
Thesis (M.L.A.) -- University of Texas at Arlington, 2008.
124

Combining Image Features For Semantic Descriptions

Soysal, Medeni 01 January 2003 (has links) (PDF)
Digital multimedia content production and the amount of content present all over the world have exploded in the recent years. The consequences of this fact can be observed everywhere in many different forms, to exemplify, huge digital video archives of broadcasting companies, commercial image archives, virtual museums, etc. In order for these sources to be useful and accessible, this technological advance must be accompanied by the effective techniques of indexing and retrieval. The most effective way of indexing is the one providing a basis for retrieval in terms of semantic concepts, upon which ordinary users of multimedia databases base their queries. On the other hand, semantic classification of images using low-level features is a challenging problem. Combining experts with different classifier structures, trained by MPEG-7low-level color and texture descriptors, is examined as a solution alternative. For combining different classifiers and features, advanced decision mechanisms are proposed, which utilize basic expert combination strategies in different settings. Each of these decision mechanisms, namely Single Feature Combination (SFC), Multiple Feature Direct Combination (MFDC), and Multiple Feature Cascaded Combination (MFCC) enjoy significant classification performance improvements over single experts. Simulations are conducted on eight different visual semantic classes, resulting in accuracy improvements between 3.5-6.5%, when they are compared with the best performance of single expert systems.
125

Indexation sémantique des images et des vidéos par apprentissage actif / Semantic indexing of images and videos by active learning.

Safadi, Bahjat 17 September 2012 (has links)
Le cadre général de cette thèse est l'indexation sémantique et la recherche d'informations, appliquée à des documents multimédias. Plus précisément, nous nous intéressons à l'indexation sémantique des concepts dans des images et vidéos par les approches d'apprentissage actif, que nous utilisons pour construire des corpus annotés. Tout au long de cette thèse, nous avons montré que les principales difficultés de cette tâche sont souvent liées, en général, à l'fossé sémantique. En outre, elles sont liées au problème de classe-déséquilibre dans les ensembles de données à grande échelle, où les concepts sont pour la plupart rares. Pour l'annotation de corpus, l'objectif principal de l'utilisation de l'apprentissage actif est d'augmenter la performance du système en utilisant que peu d'échantillons annotés que possible, ainsi minimisant les coûts de l'annotations des données (par exemple argent et temps). Dans cette thèse, nous avons contribué à plusieurs niveaux de l'indexation multimédia et nous avons proposé trois approches qui succèdent des systèmes de l'état de l'art: i) l'approche multi-apprenant (ML) qui surmonte le problème de classe-déséquilibre dans les grandes bases de données, ii) une méthode de reclassement qui améliore l'indexation vidéo, iii) nous avons évalué la normalisation en loi de puissance et de l'APC et a montré son efficacité dans l'indexation multimédia. En outre, nous avons proposé l'approche ALML qui combine le multi-apprenant avec l'apprentissage actif, et nous avons également proposé une méthode incrémentale qui accélère l'approche proposé (ALML). En outre, nous avons proposé l'approche de nettoyage actif, qui aborde la qualité des annotations. Les méthodes proposées ont été tous validées par plusieurs expériences, qui ont été menées et évaluées sur des collections à grande échelle de l'indice de benchmark internationale bien connue, appelés TRECVID. Enfin, nous avons présenté notre système d'annotation dans le monde réel basé sur l'apprentissage actif, qui a été utilisé pour mener les annotations de l'ensemble du développement de la campagne TRECVID en 2011, et nous avons présenté notre participation à la tâche d'indexation sémantique de cette campagne, dans laquelle nous nous sommes classés à la 3ème place sur 19 participants. / The general framework of this thesis is semantic indexing and information retrieval, applied to multimedia documents. More specifically, we are interested in the semantic indexing of concepts in images and videos by the active learning approaches that we use to build annotated corpus. Throughout this thesis, we have shown that the main difficulties of this task are often related, in general, to the semantic-gap. Furthermore, they are related to the class-imbalance problem in large scale datasets, where concepts are mostly sparse. For corpus annotation, the main objective of using active learning is to increase the system performance by using as few labeled samples as possible, thereby minimizing the cost of labeling data (e.g. money and time). In this thesis, we have contributed in several levels of multimedia indexing and proposed three approaches that outperform state-of-the-art systems: i) the multi-learner approach (ML) that overcomes the class-imbalance problem in large-scale datasets, ii) a re-ranking method that improves the video indexing, iii) we have evaluated the power-law normalization and the PCA and showed its effectiveness in multimedia indexing. Furthermore, we have proposed the ALML approach that combines the multi-learner with active learning, and also proposed an incremental method that speeds up ALML approach. Moreover, we have proposed the active cleaning approach, which tackles the quality of annotations. The proposed methods were validated through several experiments, which were conducted and evaluated on large-scale collections of the well-known international benchmark, called TrecVid. Finally, we have presented our real-world annotation system based on active learning, which was used to lead the annotations of the development set of TrecVid 2011 campaign, and we have presented our participation at the semantic indexing task of the mentioned campaign, in which we were ranked at the 3rd place out of 19 participants.
126

Scalable action detection in video collections / Détection scalable d'actions dans des collections vidéo

Stoian, Andrei 15 January 2016 (has links)
Cette thèse a pour but de proposer de nouvelles méthodes d'indexation des bases de données vidéo de type archive culturelle à partir des actions humaines qu'elles contiennent. Les actions humaines, représentent un aspect important des contenus multimédia, à côté des sons, images ou de la parole. L'interrogation technique principale à laquelle nous répondons est ``Comment détecter et localiser précisément et rapidement dans une vidéo une action humaine, à partir de quelques exemples de cette même action?''. Le défi relevé par cette interrogation se trouve dans la satisfaction de ces deux critères: qualité de détection et rapidité.Nous avons traité, dans une première partie, l'adaptation des mesures de similarité aux contraintes de temps de calcul et mémoire nécessaires pour avoir un système rapide de détection d'actions. Nous avons montré qu'une approche de type "alignement de séquences" couplée avec une sélection de variables permet de répondre rapidement à des requêtes et obtient une bonne qualité des résultats. L'ajout d'un filtrage préliminaire permet d'améliorer encore les performances.Dans une seconde partie de la thèse nous avons crée une méthode d'accélération de l'étage de filtrage pour obtenir une complexité de recherche sous-linéaire dans la taille de la base. Nous nous sommes basés sur le hachage sensible à la similarité et sur une nouvelle approche à l'exploration dans l'espace de hachage, adaptée à la << requête-par-détecteur >>.Nous avons testé les méthodes proposées sur une nouvelle base annotée de vidéos de grande taille destinée à la détection et localisation d'actions humaines. Nous avons montré que nos approches donnent des résultats de bonne qualité et qu'elles peuvent passer à l'échelle. / This thesis proposes new methods for indexing video collections with varied content, such as cultural archives. We focus on human actions, which represent an important cultural aspect, together with sound, images and speech. Our main technical challenge is 'How to quickly detect and precisely localize human actions in a large video collection, when these actions are given as a query through example video clips?'. Thus, the difficulty of the task is due to criteria: quality of detection and search response time.
127

EDGE-SUPPRESSED COLOR IMAGE INDEXING AND RETRIEVAL USING ANGLE-DISTANCE MEASUREMENT IN THE SCALED-SPACE OF PRINCIPAL COMPONENTS

Bobik, Sergei January 2000 (has links)
No description available.
128

Indexing presentations using multiple media streams

Ruddarraju, Ravikrishna 15 August 2006 (has links)
This thesis presents novel techniques to index multiple media streams in a digi- tally captured presentation. These media streams are related by the common content in a presentation. We use relevance curves to represent these relationships. These relevance curves are generated by using a mix of text processing techniques and distance measures for sparse vocabularies. These techniques are used to automatically detect slide boundaries in a presentation. Accuracy of detecting these boundaries is evaluated as a function of word error rates.
129

Improvement of Indexing Accuracy for Globoidal Cam Indexing Mechanisms

Ho, Hui-Chun 02 September 2003 (has links)
Globoidal cam indexing mechanism (GCIM) plays an important role in automation and machining tools. With the compact structure, a GCIM is able to reach the required precision on account of high stiffness and minimized backlash. The requirement to improve the indexing accuracy for GCIMs from industry applications drives the research going on. In this dissertation, two strategies to improve the indexing accuracy of GCIMs are proposed. The first strategy is by considering the manufacturing parameters involved in the processes of machining and assembly. Analytical expressions for the turret motion and indexing accuracy of grooved GCIMs have been identified. Based on the kinematic and geometric relationships between the cam and its roller-follower turret, the effects on the output of the cam mechanism due to clearances (between the cam and roller; in the roller bearing), preload (change of the distance between input and output shafts), and the cam taper angle have been investigated. As a result, the roller alternation in the cam-turret system can be analyzed. Favorable parameters for the design, machining, and assembly can be selected to manufacture such devices with improved turret motion and indexing accuracy. Worked examples are given to demonstrate the applications of the approach. The second strategy is a technique for designing torque balancing cam (TBC) systems that are composed of spring-loaded planar cams with translating followers for GCIMs. Such a device can be attached to the input shaft of a GCIM to reduce the variation of its cam rotational speed. As a result, for high-speed applications, the intensity of residual vibrations of a GCIM can be decreased and its indexing accuracy can be improved. To approximate the required counterbalancing torque curves, nonparametric rational B-splines have been applied to synthesize the planar cam motion programs. Experimental results have also been shown in a practical and high-speed application to prove such a TBC mechanism is useful and effective.
130

Efficiency and effectiveness of deep structure based subject indexing languages : PRECIS vs. DSIS

Biswas, Subal C. January 1988 (has links)
A 'Subject Indexing Language' (SIL) is an artificial language used for formulating names of subjects. Although classificationists have sought for universals in many fields of study such as, philosophy, biology, general systems theory, etc., the search for a deep structure of SILs formally began with Ranganathan's idea of 'absolute syntax' and was brought to the present by G. Bhattacharyya and D. Austin. Whereas Bhattacharyya's deep structure of SIL is primarily based on classificatory principles (parallel to 'absolute syntax'), the deep structure proposed by Austin has a linguistic connotation. The present study describes and compares two such deep structurebased SILs, viz., PRECIS (PREserved Context Index System) and DSIS (Deep Structure Indexing System), a recent computerized version of POPSI (POstulate-based Permuted Subject Indexing), developed by F. J. Devadason at Documentation Research and Training Centre, Bangalore, India. Both also belong to the category of SILs typified as 'string indexing' languages. The study involves: i) writing of a suitable DSIS index entry generation program, ii) using both PRECIS (in-house) and DSIS programs to index a collection of representative sample documents from the soft sciences, iii) analyzing and comparing their respective syntactic and semantic aspects in terms of both linguistic and classificatory principles, and iv) applying some measures of efficiency and effectiveness. It was realized that certain modifications in the existing DSIS string manipulation algorithms are necessary to make the program fully operational. Although, no attempts have been made to quantify the measures of effectiveness and efficiency as such, suggestions have been provided as to what these probably would be. Some indications of their searching difficulties for a prospective searcher have been put forward as well.

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