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684
Multimodality Image Registration by Maximization of Mutual Information
- IEEE TRANSACTIONS ON MEDICAL IMAGING
, 1997
"... A new approach to the problem of multimodality medical image registration is proposed, using a basic concept from information theory, mutual information (MI), or relative entropy, as a new matching criterion. The method presented in this paper applies MI to measure the statistical dependence or in ..."
Abstract
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Cited by 791 (10 self)
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A new approach to the problem of multimodality medical image registration is proposed, using a basic concept from information theory, mutual information (MI), or relative entropy, as a new matching criterion. The method presented in this paper applies MI to measure the statistical dependence
Sequence alignment and mutual information
, 810
"... Background: Alignment of biological sequences such as DNA, RNA or proteins is one of the most widely used tools in computational bioscience. All existing alignment algorithms rely on heuristic scoring schemes based on biological expertise. Therefore, these algorithms do not provide model independent ..."
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independent and objective measures for how similar two (or more) sequences actually are. Although information theory provides such a similarity measure – the mutual information (MI) – previous attempts to connect sequence alignment and information theory have not produced realistic estimates for the MI from
Mutual Online Ontology Alignment
, 2002
"... One critical foundation for reliable collective coordinated action in multi-agent systems is the ability to exchange representational objects that can be locally interpreted in ways that make collective sense. Coherent local interpretation of shared representations is needed to create global semanti ..."
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formalization and algorithm that we call mutual online ontology alignment with its rationale, and illustrates the performance of the approach with some simulation experiments.
Alignment by Maximization of Mutual Information
, 1995
"... A new information-theoretic approach is presented for finding the pose of an object in an image. The technique does not require information about the surface properties of the object, besides its shape, and is robust with respect to variations of illumination. In our derivation, few assumptions are ..."
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scenes including clutter and occlusion, tracking a human head in a video sequence and aligning a view-based 2D object model to real images. The method is based on a formulation of the mutual information between the model and the image. As applied here the technique is intensity-based, rather than
Detecting People Using Mutually Consistent Poselet Activations ⋆
"... Abstract. Bourdev and Malik (ICCV 09) introduced a new notion of parts, poselets, constructed to be tightly clustered both in the configuration space of keypoints, as well as in the appearance space of image patches. In this paper we develop a new algorithm for detecting people using poselets. Unlik ..."
Abstract
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Cited by 142 (28 self)
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are then clustered into mutually consistent hypotheses where consistency is based on empirically determined spatial keypoint distributions. Finally, bounding boxes are predicted for each person hypothesis and shape masks are aligned to edges in the image to provide a segmentation. To the best of our knowledge
Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases
- In VLDB
, 1995
"... We introduce a new model of similarity of time sequences that captures the intuitive notion that two sequences should be considered similar if they have enough non-overlapping time-ordered pairs of subsequences thar are similar. The model allows the amplitude of one of the two sequences to be scaled ..."
Abstract
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Cited by 236 (6 self)
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not be aligned along the time axis. Given this model of similarity,we present fast search techniques for discovering all similar sequences in a set of sequences. These techniques can also be used to find all (sub)sequences similar to a given sequence. We applied this matching system to the U.S. mutual funds data
A String Metric for Ontology Alignment
, 2005
"... Abstract. Ontologies are today a key part of every knowledge based system. They provide a source of shared and precisely defined terms, resulting in system interoperability by knowledge sharing and reuse. Unfortunately, the variety of ways that a domain can be conceptualized results in the creation ..."
Abstract
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Cited by 101 (2 self)
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of different ontologies with contradicting or overlapping parts. For this reason ontologies need to be brought into mutual agreement (aligned). One important method for ontology alignment is the comparison of class and property names of ontologies using stringdistance metrics. Today quite a lot of such metrics
Aligning Database Columns using Mutual Information
- In Proceedings of Conference on Digital Government Research (DG.O-05
, 2005
"... As with many large organizations, the Government's data is split in many different ways and is collected at different times by different people. The resulting massive data heterogeneity means government staff cannot effectively locate, share, or compare data across sources, let alone achieve co ..."
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Cited by 5 (0 self)
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T (Significance Information for Translation), that performs datadriven column alignments. We have applied SIfT to mapping the Santa Barbara County Air Pollution Control District’s 2001 emissions inventory database with the California Air Resources Board statewide inventory database. A fully customizable interface
Alignment of Voids in the Cosmic Web
, 2007
"... ABSTRACT We investigate the shapes and mutual alignment of voids in the large scale matter distribution of a ΛCDM cosmology simulation. The voids are identified using the novel WVF void finder technique. The identified voids are quite nonspherical and slightly prolate, with axis ratios in the order ..."
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ABSTRACT We investigate the shapes and mutual alignment of voids in the large scale matter distribution of a ΛCDM cosmology simulation. The voids are identified using the novel WVF void finder technique. The identified voids are quite nonspherical and slightly prolate, with axis ratios
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