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Medical image retrieval based on complexity analysis

BACKES, Andre R.; BRUNO, Odemir M.
Fonte: SPRINGER Publicador: SPRINGER
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
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Texture is one of the most important visual attributes used in image analysis. It is used in many content-based image retrieval systems, where it allows the identification of a larger number of images from distinct origins. This paper presents a novel approach for image analysis and retrieval based on complexity analysis. The approach consists of a texture segmentation step, performed by complexity analysis through BoxCounting fractal dimension, followed by the estimation of complexity of each computed region by multiscale fractal dimension. Experiments have been performed with MRI database in both pattern recognition and image retrieval contexts. Results show the accuracy of the method and also indicate how the performance changes as the texture segmentation process is altered.; Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP); FAPESP[2006/54367-9]; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq); CNPq[306628/2007-4]

Análise e avaliação de técnicas de interação humano-computador para sistemas de recuperação de imagens por conteúdo baseadas em estudo de caso; Evaluating human-computer interaction techniques for content-based image retrieval systems through a case study

Filardi, Ana Lúcia
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 30/08/2007 Português
Relevância na Pesquisa
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A recuperação de imagens baseada em conteúdo, amplamente conhecida como CBIR (do inglês Content-Based Image Retrieval), é um ramo da área da computação que vem crescendo muito nos últimos anos e vem contribuindo com novos desafios. Sistemas que utilizam tais técnicas propiciam o armazenamento e manipulação de grandes volumes de dados e imagens e processam operações de consultas de imagens a partir de características visuais extraídas automaticamente por meio de métodos computacionais. Esses sistemas devem prover uma interface de usuário visando uma interação fácil, natural e atraente entre o usuário e o sistema, permitindo que o usuário possa realizar suas tarefas com segurança, de modo eficiente, eficaz e com satisfação. Desse modo, o design da interface firma-se como um elemento fundamental para o sucesso de sistemas CBIR. Contudo, dentro desse contexto, a interface do usuário ainda é um elemento constituído de pouca pesquisa e desenvolvimento. Um dos obstáculos para eficácia de design desses sistemas consiste da necessidade em prover aos usuários uma interface de alta qualidade para permitir que o usuário possa consultar imagens similares a uma dada imagem de referência e visualizar os resultados. Para atingir esse objetivo...

Imagina : a cognitive abstraction approach to sketch-based image retrieval; Cognitive abstraction approach to sketch-based image retrieval

Kamvysselis, Manolis, 1977-; Marina, Ovidiu, 1975-
Fonte: Massachusetts Institute of Technology Publicador: Massachusetts Institute of Technology
Tipo: Tese de Doutorado Formato: 157 leaves; 3377346 bytes; 3377096 bytes; application/pdf; application/pdf
Português
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by Manolis Kamvysselis and Ovidiu Marina.; Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.; Includes bibliographical references (leaves 151-157).; This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.

Optimum retrieval techniques in remote sensing of atmospheric temperature, liquid water, and water vapor

Ledsham, William Henry
Fonte: Massachusetts Institute of Technology Publicador: Massachusetts Institute of Technology
Tipo: Tese de Doutorado Formato: 314 [i.e. 328] leaves; 14028075 bytes; 14027836 bytes; application/pdf; application/pdf
Português
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by William Henry Ledsham, Jr.; Thesis. 1978. Ph.D.--Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.; MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING.; Vita.; Bibliography: leaves 305-312.

A conversational interface to news retrieval

Clemens, James C. (James Charles)
Fonte: Massachusetts Institute of Technology Publicador: Massachusetts Institute of Technology
Tipo: Tese de Doutorado Formato: 53 p.
Português
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by James C. Clemens.; Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.; Includes bibliographical references (p. 51-53).

Mixed retrieval and virtual documents on the World Wide Web

Fuchs, Christopher Alan
Fonte: Massachusetts Institute of Technology Publicador: Massachusetts Institute of Technology
Tipo: Tese de Doutorado Formato: 70 leaves
Português
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by Christopher Alan Fuchs.; Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.; Includes bibliographical references (leaves 68-70).

Design and implementation of a multimedia DBMS : retrieval management

Pongsuwan, Wuttipong
Fonte: Monterey, California: Naval Postgraduate School Publicador: Monterey, California: Naval Postgraduate School
Tipo: Tese de Doutorado
Português
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Approved for public release; distribution unlimited.; Current conventional Database Management Systems (DBMS) manage only alphanumeric data. However, data to be stored in the future is expected to include some multimedia form, such as images, graphics, sounds or signals. The structure and the semantics of the media data and the operations on that data are complex. It is not clear what requirements are needed in a DBMS to manage this kind of data. It is also not clear what is needed in the data model to support this kind of data; nor what the user interface should be for such a system. The goal of the Multimedia Database Management System project in the computer science department of the Naval Post Graduate School is to build into a Database Management System (DBMS) the capability to manage multimedia data, as well as the formatted data, and define operations on multimedia data. This thesis, focusing only on the media data of image and sound, first describes the operations of such a system, then discusses the general design of it, and finally outline the detailed design and implementation of the retrieval operation.

Impact of inventory storage and retrieval schemes on productivity

Lieu, Charlene A. (Charlene Ann)
Fonte: Massachusetts Institute of Technology Publicador: Massachusetts Institute of Technology
Tipo: Tese de Doutorado Formato: 55 leaves; 3372060 bytes; 3374274 bytes; application/pdf; application/pdf
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The operational management of high volume, multi-line distribution warehouses is a monumental undertaking, which only a handful of companies in the world have chosen to tackle. Amazon.com is amongst the few, and has further differentiated itself because of its direct to customer method of distribution and complex order mixes. There is no other retailer that carries and directly delivers as many different products (over 4 million different unique items) in as wide range of product categories (from music to cosmetics to electronics to garden hoses) in as high of volume as Amazon.com. The nature of Amazon's retail model and its organic growth over the past decade has made its fulfillment centers a complex beast to decipher. Decisions on the fulfillment center floor are composed of intricate balances between demand constraints, equipment bottlenecks, storage limitations and labor costs, making the true cost associated with each variable dependent on every other variable. The goal of this thesis is to document a practical exploration of inventory storage and retrieval schemes and its relationships to productivity (and subsequently cost), as well as identify implementable changes that yields higher throughput, lower lead time for order fulfillment...

From End-User's Requirements to Web Services Retrieval: A Semantic and Intention-Driven Approach

Mirbel, Isabelle; Crescenzo, Pierre
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 23/04/2015 Português
Relevância na Pesquisa
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In this paper, we present SATIS, a framework to derive Web Service specifications from end-user's requirements in order to opera-tionalise business processes in the context of a specific application domain. The aim of SATIS is to provide to neuroscientists, which are not familiar with computer science, a complete solution to easily find a set of Web Services to implement an image processing pipeline. More precisely, our framework offers the capability to capture high-level end-user's requirements in an iterative and incremental way and to turn them into queries to retrieve Web Services description. The whole framework relies on reusable and combinable elements which can be shared out by a community of users sharing some interest or problems for a given topic. In our approach, we adopt Web semantic languages and models as a unified framework to deal with end-user's requirements and Web Service descriptions in order to take advantage of their reasoning and traceability capabilities.; Comment: {\'e}galement rapport de recherche I3S/RR--2010-03--FR in Computational Materials Science (2015). arXiv admin note: substantial text overlap with arXiv:1502.06735

Content based video retrieval

Patel, B. V.; Meshram, B. B.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 20/11/2012 Português
Relevância na Pesquisa
497.08844%
Content based video retrieval is an approach for facilitating the searching and browsing of large image collections over World Wide Web. In this approach, video analysis is conducted on low level visual properties extracted from video frame. We believed that in order to create an effective video retrieval system, visual perception must be taken into account. We conjectured that a technique which employs multiple features for indexing and retrieval would be more effective in the discrimination and search tasks of videos. In order to validate this claim, content based indexing and retrieval systems were implemented using color histogram, various texture features and other approaches. Videos were stored in Oracle 9i Database and a user study measured correctness of response.

Semantic Modeling and Retrieval of Dance Video Annotations

Kannan, Rajkumar; Ramadoss, Balakrishnan
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 04/01/2010 Português
Relevância na Pesquisa
580.70832%
Dance video is one of the important types of narrative videos with semantic rich content. This paper proposes a new meta model, Dance Video Content Model (DVCM) to represent the expressive semantics of the dance videos at multiple granularity levels. The DVCM is designed based on the concepts such as video, shot, segment, event and object, which are the components of MPEG-7 MDS. This paper introduces a new relationship type called Temporal Semantic Relationship to infer the semantic relationships between the dance video objects. Inverted file based index is created to reduce the search time of the dance queries. The effectiveness of containment queries using precision and recall is depicted. Keywords: Dance Video Annotations, Effectiveness Metrics, Metamodeling, Temporal Semantic Relationships.; Comment: INFOCOMP Journal of Computer Science, Brazil

Image Retrieval using Histogram Factorization and Contextual Similarity Learning

Liang, Liu
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
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Image retrieval has been a top topic in the field of both computer vision and machine learning for a long time. Content based image retrieval, which tries to retrieve images from a database visually similar to a query image, has attracted much attention. Two most important issues of image retrieval are the representation and ranking of the images. Recently, bag-of-words based method has shown its power as a representation method. Moreover, nonnegative matrix factorization is also a popular way to represent the data samples. In addition, contextual similarity learning has also been studied and proven to be an effective method for the ranking problem. However, these technologies have never been used together. In this paper, we developed an effective image retrieval system by representing each image using the bag-of-words method as histograms, and then apply the nonnegative matrix factorization to factorize the histograms, and finally learn the ranking score using the contextual similarity learning method. The proposed novel system is evaluated on a large scale image database and the effectiveness is shown.; Comment: 4 pages

Data Retrieval over DNS in SQL Injection Attacks

Stampar, Miroslav
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 12/03/2013 Português
Relevância na Pesquisa
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This paper describes an advanced SQL injection technique where DNS resolution process is exploited for retrieval of malicious SQL query results. Resulting DNS requests are intercepted by attackers themselves at the controlled remote name server extracting valuable data. Open source SQL injection tool sqlmap has been adjusted to automate this task. With modifications done, attackers are able to use this technique for fast and low profile data retrieval, especially in cases where other standard ones fail.; Comment: 7 pages, 3 figures, 1 table. Presented at PHDays 2012 security conference, Moscow, Russia

Data retrieval time for energy harvesting wireless sensor networks

Mitici, Mihaela; Goseling, Jasper; de Graaf, Maurits; Boucherie, Richard J.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 13/10/2015 Português
Relevância na Pesquisa
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We consider the problem of retrieving a reliable estimate of an attribute monitored by a wireless sensor network, where the sensors harvest energy from the environment independently, at random. Each sensor stores the harvested energy in batteries of limited capacity. Moreover, provided they have sufficient energy, the sensors broadcast their measurements in a decentralized fashion. Clients arrive at the sensor network according to a Poisson process and are interested in retrieving a fixed number of sensor measurements, based on which a reliable estimate is computed. We show that the time until an arbitrary sensor broadcasts has a phase-type distribution. Based on this result and the theory of order statistics of phase-type distributions, we determine the probability distribution of the time needed for a client to retrieve a reliable estimate of an attribute monitored by the sensor network. We also provide closed-form expression for the retrieval time of a reliable estimate when the capacity of the sensor battery or the rate at which energy is harvested is asymptotically large. In addition, we analyze numerically the retrieval time of a reliable estimate for various sizes of the sensor network, maximum capacity of the sensor batteries and rate at which energy is harvested. These results show that the energy harvesting rate and the broadcasting rate are the main parameters that influence the retrieval time of a reliable estimate...

Salient Local 3D Features for 3D Shape Retrieval

Godil, Afzal; Wagan, Asim Imdad
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 13/05/2011 Português
Relevância na Pesquisa
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In this paper we describe a new formulation for the 3D salient local features based on the voxel grid inspired by the Scale Invariant Feature Transform (SIFT). We use it to identify the salient keypoints (invariant points) on a 3D voxelized model and calculate invariant 3D local feature descriptors at these keypoints. We then use the bag of words approach on the 3D local features to represent the 3D models for shape retrieval. The advantages of the method are that it can be applied to rigid as well as to articulated and deformable 3D models. Finally, this approach is applied for 3D Shape Retrieval on the McGill articulated shape benchmark and then the retrieval results are presented and compared to other methods.; Comment: Three-Dimensional Imaging, Interaction, and Measurement. Edited by Beraldin, J. Angelo; Cheok, Geraldine S.; McCarthy, Michael B.; Neuschaefer-Rube, Ulrich; Baskurt, Atilla M.; McDowall, Ian E.; Dolinsky, Margaret. Proceedings of the SPIE, Volume 7864, pp. 78640S-78640S-8 (2011). Conference Location: San Francisco Airport, California, USA ISBN: 9780819484017 Date: 10 March 2011

Retrieval and Clustering from a 3D Human Database based on Body and Head Shape

Godil, Afzal; Ressler, Sandy
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 13/05/2011 Português
Relevância na Pesquisa
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In this paper, we describe a framework for similarity based retrieval and clustering from a 3D human database. Our technique is based on both body and head shape representation and the retrieval is based on similarity of both of them. The 3D human database used in our study is the CAESAR anthropometric database which contains approximately 5000 bodies. We have developed a web-based interface for specifying the queries to interact with the retrieval system. Our approach performs the similarity based retrieval in a reasonable amount of time and is a practical approach.; Comment: Published in Proceedings of the 2006 Digital Human Modeling for Design and Engineering Conference, July 2006, Lyon, FRANCE, Session: Advanced Size/Shape Analysis Paper Number: 2006-01-2355 http://papers.sae.org/2006-01-2355

Benchmarks, Performance Evaluation and Contests for 3D Shape Retrieval

Godil, Afzal; Lian, Zhouhui; Dutagaci, Helin; Fang, Rui; P., Vanamali T.; Cheung, Chun Pan
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 18/05/2011 Português
Relevância na Pesquisa
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Benchmarking of 3D Shape retrieval allows developers and researchers to compare the strengths of different algorithms on a standard dataset. Here we describe the procedures involved in developing a benchmark and issues involved. We then discuss some of the current 3D shape retrieval benchmarks efforts of our group and others. We also review the different performance evaluation measures that are developed and used by researchers in the community. After that we give an overview of the 3D shape retrieval contest (SHREC) tracks run under the EuroGraphics Workshop on 3D Object Retrieval and give details of tracks that we organized for SHREC 2010. Finally we demonstrate some of the results based on the different SHREC contest tracks and the NIST shape benchmark.; Comment: Performance Metrics for Intelligent Systems (PerMIS'10) Workshop, September, 2010

Efficient On-the-fly Category Retrieval using ConvNets and GPUs

Chatfield, Ken; Simonyan, Karen; Zisserman, Andrew
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
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We investigate the gains in precision and speed, that can be obtained by using Convolutional Networks (ConvNets) for on-the-fly retrieval - where classifiers are learnt at run time for a textual query from downloaded images, and used to rank large image or video datasets. We make three contributions: (i) we present an evaluation of state-of-the-art image representations for object category retrieval over standard benchmark datasets containing 1M+ images; (ii) we show that ConvNets can be used to obtain features which are incredibly performant, and yet much lower dimensional than previous state-of-the-art image representations, and that their dimensionality can be reduced further without loss in performance by compression using product quantization or binarization. Consequently, features with the state-of-the-art performance on large-scale datasets of millions of images can fit in the memory of even a commodity GPU card; (iii) we show that an SVM classifier can be learnt within a ConvNet framework on a GPU in parallel with downloading the new training images, allowing for a continuous refinement of the model as more images become available, and simultaneous training and ranking. The outcome is an on-the-fly system that significantly outperforms its predecessors in terms of: precision of retrieval...

A Survey of Recent View-based 3D Model Retrieval Methods

Liu, Qiong
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 08/08/2012 Português
Relevância na Pesquisa
494.027%
Extensive research efforts have been dedicated to 3D model retrieval in recent decades. Recently, view-based methods have attracted much research attention due to the high discriminative property of multi-views for 3D object representation. In this report, we summarize the view-based 3D model methods and provide the further research trends. This paper focuses on the scheme for matching between multiple views of 3D models and the application of bag-of-visual-words method in 3D model retrieval. For matching between multiple views, the many-to-many matching, probabilistic matching and semisupervised learning methods are introduced. For bag-of-visual-words application in 3D model retrieval, we first briefly review the bag-of-visual-words works on multimedia and computer vision tasks, where the visual dictionary has been detailed introduced. Then a series of 3D model retrieval methods by using bag-of-visual-words description are surveyed in this paper. At last, we summarize the further research content in view-based 3D model retrieval.; Comment: 15 pages. arXiv admin note: text overlap with arXiv:1207.7244 by other author without attribution

Cross-domain Image Retrieval with a Dual Attribute-aware Ranking Network

Huang, Junshi; Feris, Rogerio S.; Chen, Qiang; Yan, Shuicheng
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 29/05/2015 Português
Relevância na Pesquisa
492.8732%
We address the problem of cross-domain image retrieval, considering the following practical application: given a user photo depicting a clothing image, our goal is to retrieve the same or attribute-similar clothing items from online shopping stores. This is a challenging problem due to the large discrepancy between online shopping images, usually taken in ideal lighting/pose/background conditions, and user photos captured in uncontrolled conditions. To address this problem, we propose a Dual Attribute-aware Ranking Network (DARN) for retrieval feature learning. More specifically, DARN consists of two sub-networks, one for each domain, whose retrieval feature representations are driven by semantic attribute learning. We show that this attribute-guided learning is a key factor for retrieval accuracy improvement. In addition, to further align with the nature of the retrieval problem, we impose a triplet visual similarity constraint for learning to rank across the two sub-networks. Another contribution of our work is a large-scale dataset which makes the network learning feasible. We exploit customer review websites to crawl a large set of online shopping images and corresponding offline user photos with fine-grained clothing attributes...