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Automatic selection of migration velocities

by Hugh D
"... Automatic selection of reference velocities for recursive depth migration ..."
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Automatic selection of reference velocities for recursive depth migration

Feature detection with automatic scale selection

by Tony Lindeberg - International Journal of Computer Vision , 1998
"... The fact that objects in the world appear in different ways depending on the scale of observation has important implications if one aims at describing them. It shows that the notion of scale is of utmost importance when processing unknown measurement data by automatic methods. In their seminal works ..."
Abstract - Cited by 723 (34 self) - Add to MetaCart
-normalized derivatives are likely candidates to correspond to interesting structures. Specifically, it is shown how this idea can be used as a major mechanism in algorithms for automatic scale selection, which

Using Discriminant Eigenfeatures for Image Retrieval

by Daniel L. Swets, John Weng , 1996
"... This paper describes the automatic selection of features from an image training set using the theories of multi-dimensional linear discriminant analysis and the associated optimal linear projection. We demonstrate the effectiveness of these Most Discriminating Features for view-based class retrieval ..."
Abstract - Cited by 508 (15 self) - Add to MetaCart
This paper describes the automatic selection of features from an image training set using the theories of multi-dimensional linear discriminant analysis and the associated optimal linear projection. We demonstrate the effectiveness of these Most Discriminating Features for view-based class

Gene selection for cancer classification using support vector machines

by Isabelle Guyon, Jason Weston, Stephen Barnhill, Vladimir Vapnik, Nello Cristianini - Machine Learning
"... Abstract. DNA micro-arrays now permit scientists to screen thousands of genes simultaneously and determine whether those genes are active, hyperactive or silent in normal or cancerous tissue. Because these new micro-array devices generate bewildering amounts of raw data, new analytical methods must ..."
Abstract - Cited by 1115 (24 self) - Add to MetaCart
based on Recursive Feature Elimination (RFE). We demonstrate experimentally that the genes selected by our techniques yield better classification performance and are biologically relevant to cancer. In contrast with the baseline method, our method eliminates gene redundancy automatically and yields

Fast approximate nearest neighbors with automatic algorithm configuration

by Marius Muja, David G. Lowe - In VISAPP International Conference on Computer Vision Theory and Applications , 2009
"... nearest-neighbors search, randomized kd-trees, hierarchical k-means tree, clustering. For many computer vision problems, the most time consuming component consists of nearest neighbor matching in high-dimensional spaces. There are no known exact algorithms for solving these high-dimensional problems ..."
Abstract - Cited by 455 (2 self) - Add to MetaCart
-dimensional problems that are faster than linear search. Approximate algorithms are known to provide large speedups with only minor loss in accuracy, but many such algorithms have been published with only minimal guidance on selecting an algorithm and its parameters for any given problem. In this paper, we describe a

Neural networks and the automatic selection of . . .

by Duarte Trigueiros, Robert H Berry , 1991
"... In this paper we show that Neural Networks can automatically build optimal structures similar to financial ratios thus avoiding the empirically-based search of the best ratio for a given task and providing ready-to-use models based on past experience We use a well-known example to illustrate this ..."
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In this paper we show that Neural Networks can automatically build optimal structures similar to financial ratios thus avoiding the empirically-based search of the best ratio for a given task and providing ready-to-use models based on past experience We use a well-known example to illustrate

Automatic Selection of Parameters for

by Andreas Jeromin, Murat Yuksel, Shivkumar Kalyanaraman
"... Abstract — An automated method is presented for selecting optimal parameter settings for vessel/neurite segmentation algorithms using the minimum description length principle and a recursive random search algorithm. It trades off a probabilistic measure of image-content coverage, against its concise ..."
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Abstract — An automated method is presented for selecting optimal parameter settings for vessel/neurite segmentation algorithms using the minimum description length principle and a recursive random search algorithm. It trades off a probabilistic measure of image-content coverage, against its

Automatic Selection of Collocations for Instruction

by Adam Skory, Maxine Eskenazi
"... For teaching of collocations no resource exists that comprehensively ranks collocations in terms of usefulness for learners. Towards developing a method to produce such a resource, we define a collocation's utility in terms of its unpredictability; the inability of a student to derive the meani ..."
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. We intend for this research to lead to development of resources for automated content selection in CALL.

Automatic Selection of Bounding Abstractions

by Daniel S We1dd
"... Abstract Since the complexity of model-based reasoning increases drastically with the model size, automated modeling has become an active research area. However, unlike human engineers, few modeling programs introduce approximations that are customized to the question at hand. In this paper, we foc ..."
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Abstract Since the complexity of model-based reasoning increases drastically with the model size, automated modeling has become an active research area. However, unlike human engineers, few modeling programs introduce approximations that are customized to the question at hand. In this paper, we focus on a single aspect of automated model management: shifting model accuracy. We describe a domain-independent theory of query-directed model simplification that uses bounding abstractions to guarantee the accuracy of the simplifications introduced. We have tested our theory by implementing the SUP program which evaluates inequality relations in an approximate model without sacrificing accuracy. These techniques are based on our previously reported work on model sensitivity analyszs (MSA) and fitting approximations. SUP uses MSA, the subtask of predicting how a change in models will affect the resulting predicted behavior, to determine if one model is a bounding abstraction of another. Whenever two models are related by fitting approximations, the MSA computation reduces so the simple problem of computing the sign of partial derivatives in a single model, a task which is easily performed by MathematIntroduction A central problem in automated reasoning about physical systems is that the complexity of reasoning increases drastically with the size of the system descrip-

Image Inpainting

by Marcelo Bertalmio, Guillermo Sapiro , 2000
"... Inpainting, the technique of modifying an image in an undetectable form, is as ancient as art itself. The goals and applications of inpainting are numerous, from the restoration of damaged paintings and photographs to the removal/replacement of selected objects. In this paper, we introduce a novel a ..."
Abstract - Cited by 531 (25 self) - Add to MetaCart
algorithm for digital inpainting of still images that attempts to replicate the basic techniques used by professional restorators. After the user selects the regions to be restored, the algorithm automatically fills-in these regions with information surrounding them. The fill-in is done in such a way
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