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200
Geodesic Active Contours
, 1997
"... A novel scheme for the detection of object boundaries is presented. The technique is based on active contours evolving in time according to intrinsic geometric measures of the image. The evolving contours naturally split and merge, allowing the simultaneous detection of several objects and both in ..."
Abstract
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Cited by 1425 (47 self)
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A novel scheme for the detection of object boundaries is presented. The technique is based on active contours evolving in time according to intrinsic geometric measures of the image. The evolving contours naturally split and merge, allowing the simultaneous detection of several objects and both
Noname manuscript No. (will be inserted by the editor) Interleaving Distance between Merge Trees
"... the date of receipt and acceptance should be inserted later Abstract Merge trees are topological descriptors of scalar functions. They record how the subsets of the domain where the function value does not exceed a given threshold are connected. We define a distance between merge trees, called an in ..."
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the date of receipt and acceptance should be inserted later Abstract Merge trees are topological descriptors of scalar functions. They record how the subsets of the domain where the function value does not exceed a given threshold are connected. We define a distance between merge trees, called
Near neighbor search in large metric spaces
- In Proceedings of the 21th International Conference on Very Large Data Bases
, 1995
"... Given user data, one often wants to find approximate matches in a large database. A good example of such a task is finding images similar to a given image in a large collection of images. We focus on the important and technically difficult case where each data element is high dimensional, or more ge ..."
Abstract
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Cited by 216 (0 self)
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generally, is represented by a point in a large metric spaceand distance calculations are computationally expensive. In this paper we introduce a data structure to solve this problem called a GNAT- Geometric Near-neighbor Access Tree. It is based on the philosophy that the data structure should act as a
Measuring the Distance between Merge Trees
"... Abstract Merge trees represent the topology of scalar functions. To assess the topo-logical similarity of functions, one can compare their merge trees. To do so, one needs a notion of a distance between merge trees, which we define. We provide examples of using our merge tree distance and compare th ..."
Abstract
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Cited by 6 (0 self)
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Abstract Merge trees represent the topology of scalar functions. To assess the topo-logical similarity of functions, one can compare their merge trees. To do so, one needs a notion of a distance between merge trees, which we define. We provide examples of using our merge tree distance and compare
Language trees and zipping.
- PRL,
, 2002
"... In this Letter we present a very general method for extracting information from a generic string of characters, e.g., a text, a DNA sequence, or a time series. Based on data-compression techniques, its key point is the computation of a suitable measure of the remoteness of two bodies of knowledge. ..."
Abstract
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Cited by 103 (0 self)
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. On the other hand, other systems are intrinsically described by a string of characters, e.g., DNA and protein sequences, language. When analyzing a string of characters the main question is to extract the information it brings. For a DNA sequence this would correspond to the identification of the subsequences
Algorithms for merged indexes
- BTW Conf
, 2007
"... Merged indexes are B-trees that contain multiple traditional indexes and interleave their records based on a common sort order. In relational databases, merged indexes implement “master-detail clustering ” of related records, e.g., orders and order details. Thus, merged indexes shift de-normalizatio ..."
Abstract
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Cited by 1 (1 self)
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Merged indexes are B-trees that contain multiple traditional indexes and interleave their records based on a common sort order. In relational databases, merged indexes implement “master-detail clustering ” of related records, e.g., orders and order details. Thus, merged indexes shift de
Interleaved S+P Pyramidal Decomposition with Refined Prediction Model
- In ICIP
, 2005
"... Scalability and others functionalities such as the Region of Interest encoding become essential properties of an efficient image coding scheme. Within the framework of lossless compression techniques, S+P and CALIC represent the state-of-the-art. The proposed Interleaved S+P algorithm outperforms th ..."
Abstract
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Cited by 26 (19 self)
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. The image coding is done in two main steps, so that the first one supplies a LAR lowresolution image of good visual quality, and the second one allows a lossless reconstruction. The method exploits an implicit context modelling, intrinsic property of our content-based quad-tree like representation. 1.
Sequence Cluster Merging using Normalized Phylogenetic Tree Distances Towards partial requirement of L529
, 2004
"... In this report, we explain and illustrate a novel and simple method to merge sequence cluster fragments. The method uses normalized phylogenetic tree dis-tances as its base. We intend to have this method as one of the various methods that will be included in a cluster merging framework that is under ..."
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In this report, we explain and illustrate a novel and simple method to merge sequence cluster fragments. The method uses normalized phylogenetic tree dis-tances as its base. We intend to have this method as one of the various methods that will be included in a cluster merging framework
Dependency formation and directionality of tree construction
- MIT Working Papers in Linguistics 34
, 1999
"... Cyclicity effects are implemented in the Minimalist program, in part, by interleaving tree-building operations with other syntactic operations. The order of operations in the derivation is linked to the hierarchical structure of the tree, since this structure is created in the course of the derivati ..."
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Cited by 22 (0 self)
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Cyclicity effects are implemented in the Minimalist program, in part, by interleaving tree-building operations with other syntactic operations. The order of operations in the derivation is linked to the hierarchical structure of the tree, since this structure is created in the course
Bayesian hierarchical clustering
- In Proceedings of the 22nd International Conference on Machine Learning. ACM
, 2005
"... We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages over traditional distance-based agglomerative clustering algorithms. (1) It defines a probabilistic model of the data which ..."
Abstract
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Cited by 72 (11 self)
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can be used to compute the predictive distribution of a test point and the probability of it belonging to any of the existing clusters in the tree. (2) It uses a model-based criterion to decide on merging clusters rather than an ad-hoc distance metric. (3) Bayesian hypothesis testing is used to decide
Results 1 - 10
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200