Results 1 - 10 of 10,518

A density-based algorithm for discovering clusters in large spatial databases with noise

by Martin Ester, Hans-Peter Kriegel, Jörg Sander, Xiaowei Xu , 1996
"... Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large spatial databases rises the following requirements for clustering algorithms: minimal requirements of domain knowledge to determine the input parameters, discovery of clu ..."
Abstract - Cited by 1786 (70 self) - Add to MetaCart
Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large spatial databases rises the following requirements for clustering algorithms: minimal requirements of domain knowledge to determine the input parameters, discovery

Shiftable Multi-scale Transforms

by Eero Simoncelli, William T. Freeman, Edward H. Adelson, David J. Heeger , 1992
"... Orthogonal wavelet transforms have recently become a popular representation for multiscale signal and image analysis. One of the major drawbacks of these representations is their lack of translation invariance: the content of wavelet subbands is unstable under translations of the input signal. Wavel ..."
Abstract - Cited by 562 (36 self) - Add to MetaCart
. Wavelet transforms are also unstable with respect to dilations of the input signal, and in two dimensions, rotations of the input signal. We formalize these problems by defining a type of translation invariance that we call "shiftability". In the spatial domain, shiftability corresponds to a

Space-time Interest Points

by Ivan Laptev, Tony Lindeberg - IN ICCV , 2003
"... Local image features or interest points provide compact and abstract representations of patterns in an image. In this paper, we propose to extend the notion of spatial interest points into the spatio-temporal domain and show how the resulting features often reflect interesting events that can be use ..."
Abstract - Cited by 819 (21 self) - Add to MetaCart
Local image features or interest points provide compact and abstract representations of patterns in an image. In this paper, we propose to extend the notion of spatial interest points into the spatio-temporal domain and show how the resulting features often reflect interesting events that can

Unsupervised texture segmentation using Gabor filters

by Ani K. Jain, Farshid Farrokhnia - Pattern Recognition
"... We presenf a texture segmentation algorithm inspired by the multi-channel filtering theory for visual information processing in the early stages of human visual system. The channels are characterized by a bank of Gabor filters that nearly uniformly covers the spatial-frequency domain. We propose a s ..."
Abstract - Cited by 616 (20 self) - Add to MetaCart
We presenf a texture segmentation algorithm inspired by the multi-channel filtering theory for visual information processing in the early stages of human visual system. The channels are characterized by a bank of Gabor filters that nearly uniformly covers the spatial-frequency domain. We propose a

Sparse MRI: The Application of Compressed Sensing for Rapid MR Imaging

by Michael Lustig, David Donoho, John M. Pauly - MAGNETIC RESONANCE IN MEDICINE 58:1182–1195 , 2007
"... The sparsity which is implicit in MR images is exploited to significantly undersample k-space. Some MR images such as angiograms are already sparse in the pixel representation; other, more complicated images have a sparse representation in some transform domain–for example, in terms of spatial finit ..."
Abstract - Cited by 538 (11 self) - Add to MetaCart
The sparsity which is implicit in MR images is exploited to significantly undersample k-space. Some MR images such as angiograms are already sparse in the pixel representation; other, more complicated images have a sparse representation in some transform domain–for example, in terms of spatial

Fastmap: A fast algorithm for indexing, data-mining and visualization of traditional and multimedia datasets

by Christos Faloutsos, King-Ip (David) Lin , 1995
"... A very promising idea for fast searching in traditional and multimedia databases is to map objects into points in k-d space, using k feature-extraction functions, provided by a domain expert [Jag91]. Thus, we can subsequently use highly fine-tuned spatial access methods (SAMs), to answer several ..."
Abstract - Cited by 502 (22 self) - Add to MetaCart
A very promising idea for fast searching in traditional and multimedia databases is to map objects into points in k-d space, using k feature-extraction functions, provided by a domain expert [Jag91]. Thus, we can subsequently use highly fine-tuned spatial access methods (SAMs), to answer several

Max-margin Markov networks

by Ben Taskar, Carlos Guestrin, Daphne Koller , 2003
"... In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the margin of confidence of the classifier, are the method of choice for many such tasks. Their popularity stems both from the ..."
Abstract - Cited by 604 (15 self) - Add to MetaCart
the ability to use high-dimensional feature spaces, and from their strong theoretical guarantees. However, many real-world tasks involve sequential, spatial, or structured data, where multiple labels must be assigned. Existing kernel-based methods ignore structure in the problem, assigning labels

Fast Bilateral Filtering for the Display of High-Dynamic-Range Images

by Frédo Durand, Julie Dorsey , 2002
"... We present a new technique for the display of high-dynamic-range images, which reduces the contrast while preserving detail. It is based on a two-scale decomposition of the image into a base layer, encoding large-scale variations, and a detail layer. Only the base layer has its contrast reduced, the ..."
Abstract - Cited by 453 (10 self) - Add to MetaCart
, thereby preserving detail. The base layer is obtained using an edge-preserving filter called the bilateral filter. This is a non-linear filter, where the weight of each pixel is computed using a Gaussian in the spatial domain multiplied by an influence function in the intensity domain that decreases

Weighted stego-image steganalysis for JPEG covers

by Rainer Böhme - INFORMATION HIDING. LNCS 5284 , 2008
"... This paper contains two new results for the quantitative detector of LSB replacement steganography based on a weighted stegoimage (WS). First, for spatial domain steganalysis, a variant of the WS method is known to be highly accurate only when cover images have never been subject to lossy compress ..."
Abstract - Cited by 15 (2 self) - Add to MetaCart
This paper contains two new results for the quantitative detector of LSB replacement steganography based on a weighted stegoimage (WS). First, for spatial domain steganalysis, a variant of the WS method is known to be highly accurate only when cover images have never been subject to lossy

Constraint Query Languages

by Paris C. Kanellakis , Gabriel M. Kuper, Peter Z. Revesz , 1992
"... We investigate the relationship between programming with constraints and database query languages. We show that efficient, declarative database programming can be combined with efficient constraint solving. The key intuition is that the generalization of a ground fact, or tuple, is a conjunction ..."
Abstract - Cited by 372 (43 self) - Add to MetaCart
of constraints over a small number of variables. We describe the basic Constraint Query Language design principles and illustrate them with four classes of constraints: real polynomial inequalities, dense linear order inequalities, equalities over an infinite domain, and boolean equalities. For the analysis
Results 1 - 10 of 10,518