Results 11 - 20 of 494

Segmentation as Maximum-Weight Independent Set

by William Brendel, Sinisa Todorovic
"... Given an ensemble of distinct, low-level segmentations of an image, our goal is to identify visually “meaningful ” segments in the ensemble. Knowledge about any specific objects and surfaces present in the image is not available. The selection of image regions occupied by objects is formalized as th ..."
Abstract - Cited by 19 (0 self) - Add to MetaCart
. The algorithm is shown to converge to an optimum. Our empirical evaluation on the benchmark Berkeley segmentation dataset shows that the new algorithm eliminates the need for hand-picking optimal input parameters of the state-of-the-art segmenters, and outperforms their best, manually optimized results. 1

Does Corporate Diversification Destroy Value

by John R. Graham, Michael L. Lemmon, Jack G. Wolf - Journal of Finance , 2002
"... We analyze several hundred firms that expand via acquisition and0or increase their number of business segments. The combined market reaction to acquisition announcements is positive but acquiring firm excess values decline after the diversifying event. Much of the excess value reduction occurs becau ..."
Abstract - Cited by 117 (2 self) - Add to MetaCart
because our sample firms acquire already discounted business units, and not because diversifying destroys value. This implies that the standard assumption that conglomerate divisions can be benchmarked to typical stand-alone firms should be carefully reconsidered. We also show that excess value does

Accelerated Profile HMM Searches

by Sean R. Eddy , 2011
"... Profile hidden Markov models (profile HMMs) and probabilistic inference methods have made important contributions to the theory of sequence database homology search. However, practical use of profile HMM methods has been hindered by the computational expense of existing software implementations. Her ..."
Abstract - Cited by 113 (6 self) - Add to MetaCart
method I call ‘‘sparse rescaling’’. These methods are assembled in a pipeline in which high-scoring MSV hits are passed on for reanalysis with the full HMM Forward/Backward algorithm. This accelerated pipeline is implemented in the freely available HMMER3 software package. Performance benchmarks show

Comparative testing of DNA segmentation algorithms using benchmark simulations,

by Eran Elhaik , Dan Graur , Krešimir Josić - Mol. Biol. Evol. , 2010
"... Abstract Numerous segmentation methods for the detection of compositionally homogeneous domains within genomic sequences have been proposed. Unfortunately, these methods yield inconsistent results. Here, we present a benchmark consisting of two sets of simulated genomic sequences for testing the pe ..."
Abstract - Cited by 3 (1 self) - Add to MetaCart
Abstract Numerous segmentation methods for the detection of compositionally homogeneous domains within genomic sequences have been proposed. Unfortunately, these methods yield inconsistent results. Here, we present a benchmark consisting of two sets of simulated genomic sequences for testing

Joint shape segmentation with linear programming

by Qixing Huang, Vladlen Koltun, Leonidas Guibas - ACM Trans. on Graphics (Proc. SIGGRAPH Asia , 2011
"... We present an approach to segmenting shapes in a heterogenous shape database. Our approach segments the shapes jointly, utilizing features from multiple shapes to improve the segmentation of each. The approach is entirely unsupervised and is based on an integer quadratic programming formulation of t ..."
Abstract - Cited by 43 (4 self) - Add to MetaCart
that makes the optimization feasible for large databases. We evaluate the presented approach on the Princeton segmentation benchmark and show that joint shape segmentation significantly outperforms single-shape segmentation techniques.

Unsupervised Segmentation of Natural Images via Lossy Data Compression

by Allen Y. Yang, John Wright, Shankar Sastry, Yi Ma , 2007
"... In this paper, we cast natural-image segmentation as a problem of clustering texture features as multivariate mixed data. We model the distribution of the texture features using a mixture of Gaussian distributions. Unlike most existing clustering methods, we allow the mixture components to be degene ..."
Abstract - Cited by 60 (3 self) - Add to MetaCart
to be degenerate or nearly-degenerate. We contend that this assumption is particularly important for mid-level image segmentation, where degeneracy is typically introduced by using a common feature representation for different textures in an image. We show that such a mixture distribution can be effectively

Image Segmentation by Uniform Color Clustering Approach and Benchmark Results

by Gerald Friedl, Kristian Jantz, Raul Rojas
"... Abstract. The following article presents an approach for interactive foreground extraction in still images. The presented approach has been derived from color signatures, a technique originated from image retrieval. The article explains the algorithm and presents some benchmark results to show the i ..."
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Abstract. The following article presents an approach for interactive foreground extraction in still images. The presented approach has been derived from color signatures, a technique originated from image retrieval. The article explains the algorithm and presents some benchmark results to show

Probabilistic image segmentation with closedness constraints

by Bjoern Andres, Thorsten Beier, Ullrich Köthe, Fred A. Hamprecht - In ICCV , 2011
"... We propose a novel graphical model for probabilistic image segmentation that contributes both to aspects of perceptual grouping in connection with image segmentation, and to globally optimal inference with higher-order graphical models. We represent image partitions in terms of cellular complexes in ..."
Abstract - Cited by 29 (14 self) - Add to MetaCart
on perceptually meaningful segmentations. We give a complete polyhedral characterization of the resulting global inference problem in terms of the multicut polytope and efficiently compute global optima by a cutting plane method. Competitive results for the Berkeley segmentation benchmark confirm the consistency

Quantitative evaluation of a novel image segmentation algorithm

by Francisco J. Estrada, Allan D. Jepson - In IEEE Conference on Computer Vision and Pattern Recognition , 2005
"... We present a quantitative evaluation of SE-MinCut, a novel segmentation algorithm based on spectral embedding and minimum cut. We use human segmentations from the Berkeley Segmentation Database as ground truth and propose suitable measures to evaluate segmentation quality. With these measures we gen ..."
Abstract - Cited by 38 (4 self) - Add to MetaCart
We present a quantitative evaluation of SE-MinCut, a novel segmentation algorithm based on spectral embedding and minimum cut. We use human segmentations from the Berkeley Segmentation Database as ground truth and propose suitable measures to evaluate segmentation quality. With these measures we

Robust Path-Based Spectral Clustering with Application to Image Segmentation

by Hong Chang, Dit-Yan Yeung
"... Spectral clustering and path-based clustering are two recently developed clustering approaches that have delivered impressive results in a number of challenging clustering tasks. However, they are not robust enough against noise and outliers in the data. In this paper, based on M-estimation from rob ..."
Abstract - Cited by 15 (2 self) - Add to MetaCart
and real-world data, comparing our method with some other methods. In particular, color images from the Berkeley Segmentation Dataset and Benchmark are used in the image segmentation experiments. Experimental results show that our method consistently outperforms other methods due to its higher robustness.
Results 11 - 20 of 494