Results 1  10
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2,486
A Geometric Alternative to Computed Tomography
, 1991
"... This paper describes a totally new way to process Xray data in order to reconstruct the external and internal boundaries of objects, which do not involve Computed Tomography (CT). We show that the segmentation can be performed directly with the raw data, the sinogram produced with the scanner, a ..."
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Cited by 1 (0 self)
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, and that those segmented shapes can be geometrically transformed into reconstructed shapes in the usual space. Thus, if we are interested in only the boundaries of the objects, our method eliminates the computationally expensive step of Computed Tomography. Experimental results are presented for both
DavenportSchinzel Sequences and Their Geometric Applications
, 1998
"... An (n; s) DavenportSchinzel sequence, for positive integers n and s, is a sequence composed of n distinct symbols with the properties that no two adjacent elements are equal, and that it does not contain, as a (possibly noncontiguous) subsequence, any alternation a \Delta \Delta \Delta b \Delta \ ..."
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Cited by 439 (105 self)
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An (n; s) DavenportSchinzel sequence, for positive integers n and s, is a sequence composed of n distinct symbols with the properties that no two adjacent elements are equal, and that it does not contain, as a (possibly noncontiguous) subsequence, any alternation a \Delta \Delta \Delta b \Delta
Visual categorization with bags of keypoints
 In Workshop on Statistical Learning in Computer Vision, ECCV
, 2004
"... Abstract. We present a novel method for generic visual categorization: the problem of identifying the object content of natural images while generalizing across variations inherent to the object class. This bag of keypoints method is based on vector quantization of affine invariant descriptors of im ..."
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Cited by 1005 (14 self)
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of image patches. We propose and compare two alternative implementations using different classifiers: Naïve Bayes and SVM. The main advantages of the method are that it is simple, computationally efficient and intrinsically invariant. We present results for simultaneously classifying seven semantic visual
PERIODIC SEQUENCES OF NUMBERS IN GENERALIZED ARITHMETIC AND GEOMETRIC ALTERNATE PROGRESSIONS
, 2015
"... MSC 2010 Classifications: Primary 11B25; Secondary 11Y55. Sequence of numbers with alternate common difference and ratio, general term an, periodic sequence, sum. Abstract The paper provides a generalization of the arithmeticgeometric alternate sequence introduced recently by Rabago ..."
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MSC 2010 Classifications: Primary 11B25; Secondary 11Y55. Sequence of numbers with alternate common difference and ratio, general term an, periodic sequence, sum. Abstract The paper provides a generalization of the arithmeticgeometric alternate sequence introduced recently by Rabago
Efficient algorithms for geometric optimization
 ACM Comput. Surv
, 1998
"... We review the recent progress in the design of efficient algorithms for various problems in geometric optimization. We present several techniques used to attack these problems, such as parametric searching, geometric alternatives to parametric searching, pruneandsearch techniques for linear progra ..."
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Cited by 114 (10 self)
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We review the recent progress in the design of efficient algorithms for various problems in geometric optimization. We present several techniques used to attack these problems, such as parametric searching, geometric alternatives to parametric searching, pruneandsearch techniques for linear
Metric Learning by Collapsing Classes
"... We present an algorithm for learning a quadratic Gaussian metric (Mahalanobis distance) for use in classification tasks. Our method relies on the simple geometric intuition that a good metric is one under which points in the same class are simultaneously near each other and far from points in th ..."
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Cited by 230 (2 self)
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We present an algorithm for learning a quadratic Gaussian metric (Mahalanobis distance) for use in classification tasks. Our method relies on the simple geometric intuition that a good metric is one under which points in the same class are simultaneously near each other and far from points
Support vector machines: Training and applications
 A.I. MEMO 1602, MIT A. I. LAB
, 1997
"... The Support Vector Machine (SVM) is a new and very promising classification technique developed by Vapnik and his group at AT&T Bell Laboratories [3, 6, 8, 24]. This new learning algorithm can be seen as an alternative training technique for Polynomial, Radial Basis Function and MultiLayer Perc ..."
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Cited by 223 (3 self)
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The Support Vector Machine (SVM) is a new and very promising classification technique developed by Vapnik and his group at AT&T Bell Laboratories [3, 6, 8, 24]. This new learning algorithm can be seen as an alternative training technique for Polynomial, Radial Basis Function and Multi
Towards Exact Geometric Computation
, 1994
"... Exact computation is assumed in most algorithms in computational geometry. In practice, implementors perform computation in some fixedprecision model, usually the machine floatingpoint arithmetic. Such implementations have many wellknown problems, here informally called "robustness issues&quo ..."
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Cited by 96 (6 self)
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viable alternative. It turns out that the exact computation paradigm encomp...
An ImageBased Approach to ThreeDimensional Computer Graphics
, 1997
"... The conventional approach to threedimensional computer graphics produces images from geometric scene descriptions by simulating the interaction of light with matter. My research explores an alternative approach that replaces the geometric scene description with perspective images and replaces the s ..."
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Cited by 207 (5 self)
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The conventional approach to threedimensional computer graphics produces images from geometric scene descriptions by simulating the interaction of light with matter. My research explores an alternative approach that replaces the geometric scene description with perspective images and replaces
Global land cover mapping from MODIS: algorithms and early results,
 Remote Sensing of Environment,
, 2002
"... Abstract Until recently, advanced very highresolution radiometer (AVHRR) observations were the only viable source of data for global land cover mapping. While many useful insights have been gained from analyses based on AVHRR data, the availability of moderate resolution imaging spectroradiometer ..."
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Cited by 212 (8 self)
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(MODIS) data with greatly improved spectral, spatial, geometric, and radiometric attributes provides significant new opportunities and challenges for remote sensingbased land cover mapping research. In this paper, we describe the algorithms and databases being used to produce the MODIS global land cover
Results 1  10
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2,486