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检索条件"主题词=Query by example"

共 106 条记录，以下是81-90 订阅

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Interactive Retrieval of Spoken Content Optimizing by LDA Algorithm

Interactive Retrieval of Spoken Content Optimizing by LDA Al...

引用

International Conference on Intelligent Computing and Control (I2C2)

作者： Chavan, Sayali S. Kagalkar, Ramesh Dr DYP Sch Engn & Technol Dept Comp Engn Pune Maharashtra India

ISBN: (纸本)9781538603741

Communication between the human are performed by using different languages. Language is either in written or spoken form. In our paper, as an author we are representing a framework that gives output as a description for audio file using signal processing. The output is in the text format which is derived by examining the audio content and providing the description of audio in the text format. So the study of translation of audio into text goes increasing. The framework is distributed into two sections called training and testing section. The training section is train the audio with its description like speech conversation present in that audio. This data is stored in the system using database with features of scenario of audio. Another section is testing section. The testing section test the audio file and retrieve the output as description of audio comparing audios stored into database (i.e. in training section). Using Latent Dirichlet allocation processing sentences are generated from objects and their activities.

关键词： Spoken content retrieval spoken term detection query by example semantic retrieval joint optimization pseudo-relevance feedback graph-based random walk unsupervised acoustic pattern discovery query expansion interactive retrieval summarization key term extraction

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Speech audio retrieval using voice query

引用

9th International Conference on Asian Digital Libraries

作者： Ratanamahatana, Chotirat Ann Tohlong, Phubes Chulalongkorn Univ Dept Comp Engn Bangkok 10330 Thailand

ISBN: (纸本)3540493751

Multimedia data has increasingly become a prevalent resource in Digital Library system;this includes audio, video, and image archives. However, each type of these data may need specific tools to help facilitate effective and efficient retrieval tasks. In this paper, we focus on retrieval of speech audio collection, which includes audio books, speech recordings, interviews, and lectures. Currently, most of the audio retrieval systems are based on keyword/title/author search typed into the system by users. The system then searches for particular keywords and gives a list of entire audio files that potentially are relevant to the query. Nonetheless, browsing audio content for particular section of the audios without knowing the actual content is yet a very difficult task. Moreover, since audio transcription or keyword annotation is very labor intensive and becomes infeasible for large data, we introduce here a prelimnary framework that locates subsections of the audio that correspond to the voice query made by a user. We demonstrate a utility of our approach on query retrieval tasks in various types of audio recordings. We also show that this simple framework can potentially help retrieve and locate the voice query within the audio accurately and efficiently.

关键词： audio retrieval time series query by example voice search

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Online multimodal matrix factorization for human action video indexing

Online multimodal matrix factorization for human action vide...

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12th International Workshop on Content-Based Multimedia Indexing (CBMI)

作者： Paez, Fabian Vanegas, Jorge A. Gonzalez, Fabio A. Univ Nacl Colombia MindLAB Res Grp Bogota Colombia

ISBN: (纸本)9781479939909

This paper addresses the problem of searching for videos containing instances of specific human actions. The proposed strategy builds a multimodal latent space representation where both visual content and annotations are simultaneously mapped. The hypothesis behind the method is that such a latent space yields better results when built from multiple data modalities. The semantic embedding is learned using matrix factorization through stochastic gradient descent, which makes it suitable to deal with large-scale collections. The method is evaluated on a large-scale human action video dataset with three modalities corresponding to action labels, action attributes and visual features. The evaluation is based on a query-by-example strategy, where a sample video is used as input to the system. A retrieved video is considered relevant if it contains an instance of the same human action present in the query. Experimental results show that the learned multimodal latent semantic representation produces improved performance when compared with an exclusively visual representation.

关键词： Matrix factorization multimodal data information retrieval query by example video processing human actions latent space

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Histogram Intersection based Image Retrieval Technique using Relevance Feedback

Histogram Intersection based Image Retrieval Technique using...

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3rd International Workshop on Soft Computing Applications

作者： Barbu, Tudor Costin, Mihaela Ciobanu, Adrian Romanian Acad Inst Comp Sci Iasi Branch Iasi Romania

ISBN: (纸本)9781424450541

This article provides a color-based image retrieval technique for RGB image databases. Our proposed CBIR system uses the query by example approach and a relevance feedback mechanism. Feature extraction process is performed by computing a global color histogram for each image. Feature vectors are compared using the histogram intersection difference metric, and a relevance feedback mechanism is used in the retrieval process.

关键词： RGB image image base CBIR color-based image retrieval color histogram feature vector histogram intersection query by example relevance feedback

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Two-level clustering towards unsupervised discovery of acoustic classes

Two-level clustering towards unsupervised discovery of acous...

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12th International Conference on Machine Learning and Applications (ICMLA)

作者： Gracia, Ciro Anguera, Xavier Binefa, Xavier Univ Pompeu Fabra Dept Informat & Commun Technol Barcelona Spain Telefon Res Barcelona Spain

ISBN: (纸本)9780769551449

In this paper we focus on unsupervised discovering of acoustic classes suitable for use in pattern recognition applications. Our approach is based on a two-level clustering of an initial acoustic segmentation of the audio data in order to allow for discovery and correct modeling of complex acoustic classes. Initially, in a first-level, the acoustic space is densely clustered in order to provide a first layer of acoustic variance reduction. In a second-level clustering we use the acoustic segmentation to infer a smaller number of super-clusters taking advantage of the intra-segment relationships between the first-level clusters. In this paper we compare three possible clustering methods to obtain super-clusters as sub-sets or linear combinations of first-level clusters. Results indicate that the proposed two-level approach improves the balance between Purity and inverse Purity evaluation measures while significantly improving the stability of the transcriptions obtained when using the resulting models to transcribe the same acoustic events in different spoken utterances.

关键词： zero resources clustering query by example

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Duoquest: A Dual-Specification System for Expressive SQL Queries 20

Duoquest: A Dual-Specification System for Expressive SQL Que...

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ACM SIGMOD International Conference on Management of Data (SIGMOD)

作者： Baik, Christopher Jin, Zhongjun Cafarella, Michael Jagadish, H., V Univ Michigan Ann Arbor MI 48109 USA

ISBN: (纸本)9781450367356

querying a relational database is difficult because it requires users to be familiar with both the SQL language and the schema. However, many users possess enough domain expertise to describe their desired queries by alternative means. For such users, two major alternatives to writing SQL are natural language interfaces (NLIs) and programming-by-example (PBE). Both of these alternatives face certain pitfalls: natural language queries (NLQs) are often ambiguous, even for human interpreters, while current PBE approaches limit functionality to be tractable. Consequently, we propose dual-specification query synthesis, which consumes both a NLQ and an optional PBE-like table sketch query that enables users to express varied levels of domain knowledge. We introduce the novel dual-specification Duoqest system, which leverages guided partial query enumeration to efficiently explore the space of possible queries. We present results from user studies in which Duoqest demonstrates a 62.5% absolute increase in query construction accuracy over a state-of-the-art NLI and comparable accuracy to a PBE system on a limited workload supported by the PBE system. In a simulation study on the Spider benchmark, Duoqest demonstrates a >2x increase in top-1 accuracy over both NLI and PBE.

关键词： database usability query by example SQL program synthesis dual-specification interface

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Video Clip Retrieval Based on LBP Variance 12

Video Clip Retrieval Based on LBP Variance

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12th International Conference on Communication Networks (ICCN) / 12th International Conference on Data Mining and Warehousing (ICDMW) / 12th International Conference on Image and Signal Processing (ICISP)

作者： Shekar, B. H. Uma, K. P. Holla, K. Raghurama Mangalore Univ Mangalore Karnataka India

Advancement in technology has made the acquisition and storage of multimedia data easy and inexpensive to the end user. However for effective use of the information available in the multimedia, efficient and accurate retrieval methods are required. Multimedia based retrieval systems extensively used texture based approach to interpret and recognize a scene image. The texture of an image provides clue to the orientation, smoothness, symmetry, shape, regularity and coarness of the surface. The Local Binary Pattern Variance (LBPV) is a texture feature where variance in contrast acts as adaptive factor during computation of local binary pattern (LBP) histogram. The LBP combines both structural and statistical approaches to texture analysis. This paper proposes an LBP Variance based approach to visual content based video retrieval. The proposed approach uses query by example paradigm for retrieving similar clips from the video. Experiments conducted on TRECVID dataset shows the efficacy of proposed approach. (C) 2016 The Authors. Published by Elsevier B.V.

关键词： Content Based Retrieval Local Binary Pattern Variance Multimedia query by example

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CONTENT-BASED REPRESENTATIONS OF AUDIO USING SIAMESE NEURAL NETWORKS

CONTENT-BASED REPRESENTATIONS OF AUDIO USING SIAMESE NEURAL ...

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IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Manocha, Pranay Badlani, Rohan Kumar, Anurag Shah, Ankit Elizalde, Benjamin Raj, Bhiksha IIT Guwahati Dept Elect & Elect Engn Gauhati India BITS Pilani Dept Comp Sci Hyderabad Telangana India Carnegie Mellon Univ Language Technol Inst Pittsburgh PA 15213 USA

ISBN: (纸本)9781538646588

In this paper, we focus on the problem of content-based retrieval for audio, which aims to retrieve all semantically similar audio recordings for a given audio clip query. This problem is similar to the problem of query by example of audio, which aims to retrieve media samples from a database, which are similar to the user-provided example. We propose a novel approach which encodes the audio into a vector representation using Siamese Neural Networks. The goal is to obtain an encoding similar for files belonging to the same audio class, thus allowing retrieval of semantically similar audio. Using simple similarity measures such as those based on simple euclidean distance and cosine similarity we show that these representations can be very effectively used for retrieving recordings similar in audio content.

关键词： Audio Fingerprinting Content-Based Retrieval query by example Siamese Network Similar Matching

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WISE: A content-based Web image search engine

WISE: A content-based Web image search engine

引用

Conference on Multimedia Computing and Networking 2001

作者： Qiu, G Palmer, RD Univ Leeds Sch Comp Leeds LS2 9JT W Yorkshire England

ISBN: (纸本)0819439908

This paper describes the development of a prototype of a Web Image Search Engine (WISE), which allows users to search for images on the WWW by image examples, in a similar fashion to current search engines that allow users to find related Web pages using text matching on keywords. The system takes an image specified by the user and finds similar images available on the WWW by comparing the image contents using low level image features. The current version of the WISE system consists of a graphical user interface (GUI), an autonomous Web agent, an image comparison program and a query processing program. The users specify the URL of a target image and the URL of the starting Web page from where the proram will "crawl" the Web, finding images along the way and retrieve those satisfying a certain constraints. The program then computes the visual features of the retrieved images and performs content-based comparison with the target image. The results of the comparison are then sorted according to a certain similarity measure, which along with thumbnails and information associated with the images, such as the URLs;image size, etc. are then written to an HTML page. The resultant page is stored on a Web server and is outputted onto the user's Web browser once the search process is complete. A unique feature of the current version of WISE is its image content comparison algorithm. It is based on the comparison of image palettes [6] and it therefore very efficient in retrieving one of the two universally accepted image formats on the Web, "gif". In gif images, the colour palette is contained in its header and therefore it is only necessary to retrieve the header information rather than the whole image, thus making it very efficient.

关键词： search engines content-based image indexing and retrieval (CBIR) image database query by example

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Boosting the handwritten word spotting experience by including the user in the loop

Boosting the handwritten word spotting experience by includi...

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作者： Rusiñol, Marçal Lladós, Josep Computer Vision Center Dept. Ciències de la Computació Univ. Autònoma de Barcelona 08193 Bellaterra Barcelona Spain

In this paper, we study the effect of taking the user into account in a query-by-example handwritten word spotting framework. Several off-the-shelf query fusion and relevance feedback strategies have been tested in the handwritten word spotting context. The increase in terms of precision when the user is included in the loop is assessed using two datasets of historical handwritten documents and two baseline word spotting approaches both based on the bag-of-visual-words model. We finally present two alternative ways of presenting the results to the user that might be more attractive and suitable to the user's needs than the classic ranked list. © 2013 Elsevier Ltd. All rights reserved.

关键词： Handwritten word spotting Multidimensional scaling query by example query fusion Relevance feedback

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