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148,306
Evaluation of different segmentation techniques for dialogue turns
"... In dialogue systems, it is necessary to decode the user input into semantically meaningful units. These semantical units, usually Dialogue Acts (DA), are used by the system to produce the most appropriate response. The user turns can be segmented into utterances, which are meaningful segments from t ..."
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on a Spanish dialogue system on a railway information task. The results reveal that one of these techniques provides a high quality segmentation for this corpus. 1.
A Comparative Study of Different Segmentation Techniques for
"... Abstract: Brain tumour detection is one of the challenging tasks in medical image processing. The present study discusses in detail the segmentation process by means of histogram clustering, Global thresholding, Watershed segmentation and edge based segmentation. Six MRI images from radiologists wer ..."
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Abstract: Brain tumour detection is one of the challenging tasks in medical image processing. The present study discusses in detail the segmentation process by means of histogram clustering, Global thresholding, Watershed segmentation and edge based segmentation. Six MRI images from radiologists
Implementation and Comparison of Different Segmentation Techniques for Medical Images
"... Segmentation is an important concept in image processing with an objective of dividing the image into regions and characterizes the structures with some input features, so that the output image is meaningful and easier to analyze. A large number of algorithms have been proposed in various applicatio ..."
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segmentation is done using the K-Means, Fuzzy C-Means, Otsu Thresholding and morphological closing and reconstruction. Performance measuring parameters such as Structural content, mean square value, peak to signal ratio, Average difference Results obtained are satisfactory
Comparative Analysis of Brain Tumor Detection using Different Segmentation Techniques
"... In this study, we would like to present brain tumor detection methods, based on the conventional K-means technique, Expectation Maximization (EM) algorithm and a new Spatial Fuzzy-technique analysis of brain MR images. Though, the K-means and EM algorithm were already used in Brain MR image segmenta ..."
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segmentation, as well as image segmentation in general, it fails to utilize the strong spatial correlation between neighboring pixels. A spatial Fuzzy C-means (SFCM’s) technique, which is utilize the spatial information properly and produce high quality segmentation of brain tumor images. Five ground truth
Efficient graph-based image segmentation.
- International Journal of Computer Vision,
, 2004
"... Abstract. This paper addresses the problem of segmenting an image into regions. We define a predicate for measuring the evidence for a boundary between two regions using a graph-based representation of the image. We then develop an efficient segmentation algorithm based on this predicate, and show ..."
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Cited by 940 (1 self)
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that although this algorithm makes greedy decisions it produces segmentations that satisfy global properties. We apply the algorithm to image segmentation using two different kinds of local neighborhoods in constructing the graph, and illustrate the results with both real and synthetic images. The algorithm
A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics
- in Proc. 8th Int’l Conf. Computer Vision
, 2001
"... This paper presents a database containing ‘ground truth ’ segmentations produced by humans for images of a wide variety of natural scenes. We define an error measure which quantifies the consistency between segmentations of differing granularities and find that different human segmentations of the s ..."
Abstract
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Cited by 954 (14 self)
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This paper presents a database containing ‘ground truth ’ segmentations produced by humans for images of a wide variety of natural scenes. We define an error measure which quantifies the consistency between segmentations of differing granularities and find that different human segmentations
Performance of optical flow techniques
- INTERNATIONAL JOURNAL OF COMPUTER VISION
, 1994
"... While different optical flow techniques continue to appear, there has been a lack of quantitative evaluation of existing methods. For a common set of real and synthetic image sequences, we report the results of a number of regularly cited optical flow techniques, including instances of differential, ..."
Abstract
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Cited by 1325 (32 self)
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While different optical flow techniques continue to appear, there has been a lack of quantitative evaluation of existing methods. For a common set of real and synthetic image sequences, we report the results of a number of regularly cited optical flow techniques, including instances of differential
A Survey of Image Registration Techniques
- ACM Computing Surveys
, 1992
"... Registration is a fundamental task in image processing used to match two or more pictures taken, for example, at different times, from different sensors or from different viewpoints. Over the years, a broad range of techniques have been developed for the various types of data and problems. These ..."
Abstract
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Cited by 979 (2 self)
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Registration is a fundamental task in image processing used to match two or more pictures taken, for example, at different times, from different sensors or from different viewpoints. Over the years, a broad range of techniques have been developed for the various types of data and problems
A Survey of Program Slicing Techniques
- JOURNAL OF PROGRAMMING LANGUAGES
, 1995
"... A program slice consists of the parts of a program that (potentially) affect the values computed at some point of interest, referred to as a slicing criterion. The task of computing program slices is called program slicing. The original definition of a program slice was presented by Weiser in 197 ..."
Abstract
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Cited by 790 (10 self)
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in 1979. Since then, various slightly different notions of program slices have been proposed, as well as a number of methods to compute them. An important distinction is that between a static and a dynamic slice. The former notion is computed without making assumptions regarding a program's input
MATRIX FACTORIZATION TECHNIQUES FOR RECOMMENDER SYSTEMS
- IEEE COMPUTER
, 2009
"... As the Netflix Prize competition has demonstrated, matrix factorization models are superior to classic nearest-neighbor techniques for producing product recommendations, allowing the incorporation of additional information such as implicit feedback, temporal effects, and confidence levels. Modern co ..."
Abstract
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Cited by 593 (4 self)
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As the Netflix Prize competition has demonstrated, matrix factorization models are superior to classic nearest-neighbor techniques for producing product recommendations, allowing the incorporation of additional information such as implicit feedback, temporal effects, and confidence levels. Modern
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