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Where the REALLY Hard Problems Are
- IN J. MYLOPOULOS AND R. REITER (EDS.), PROCEEDINGS OF 12TH INTERNATIONAL JOINT CONFERENCE ON AI (IJCAI-91),VOLUME 1
, 1991
"... It is well known that for many NP-complete problems, such as K-Sat, etc., typical cases are easy to solve; so that computationally hard cases must be rare (assuming P != NP). This paper shows that NP-complete problems can be summarized by at least one "order parameter", and that the hard p ..."
Abstract
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Cited by 683 (1 self)
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problems occur at a critical value of such a parameter. This critical value separates two regions of characteristically different properties. For example, for K-colorability, the critical value separates overconstrained from underconstrained random graphs, and it marks the value at which the probability
Rapid object detection using a boosted cascade of simple features
- ACCEPTED CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION 2001
, 2001
"... This paper describes a machine learning approach for visual object detection which is capable of processing images extremely rapidly and achieving high detection rates. This work is distinguished by three key contributions. The first is the introduction of a new image representation called the " ..."
Abstract
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Cited by 3283 (9 self)
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the "Integral Image" which allows the features used by our detector to be computed very quickly. The second is a learning algorithm, based on AdaBoost, which selects a small number of critical visual features from a larger set and yields extremely efficient classifiers[6]. The third contribution
Robust Real-time Object Detection
- International Journal of Computer Vision
, 2001
"... This paper describes a visual object detection framework that is capable of processing images extremely rapidly while achieving high detection rates. There are three key contributions. The first is the introduction of a new image representation called the “Integral Image ” which allows the features ..."
Abstract
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Cited by 1184 (4 self)
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used by our detector to be computed very quickly. The second is a learning algorithm, based on AdaBoost, which selects a small number of critical visual features and yields extremely efficient classifiers [6]. The third contribution is a method for combining classifiers in a “cascade ” which allows
Thermodiffusion in the Critical Region
"... Abstract. Long range fluctuations of the order parameter affect thermodynamic as well as transport properties in the critical region. The values of transport coefficients near a critical point are typically enhanced compared to the values in the classical region far away from a critical point. Asymp ..."
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Abstract. Long range fluctuations of the order parameter affect thermodynamic as well as transport properties in the critical region. The values of transport coefficients near a critical point are typically enhanced compared to the values in the classical region far away from a critical point
Concrete Resistance: Ando in the context of critical regionalism
, 2006
"... Critical regionalism was first introduced as an architectural concept in the early 1980s in ..."
Abstract
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Cited by 1 (0 self)
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Critical regionalism was first introduced as an architectural concept in the early 1980s in
Finding critical regions in a network
"... It is important that our vital networks (e.g., infrastructures) are robust to more than single-link failures. Failures might for instance affect a part of the network that resides in a certain geographical region. In this paper, considering networks embedded in a two-dimensional plane, we study the ..."
Abstract
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Cited by 2 (1 self)
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the problem of finding a critical region- that is, a part of the network that can be enclosed by a given elementary figure (a circle, ellipse, rectangle, square, or equilateral triangle) with a predetermined size- whose removal would lead to the highest network disruption. We determine that there is a
Detecting Critical Regions in Scalar Fields
, 2003
"... Trivariate data is commonly visualized using isosurfaces or direct volume rendering. When exploring scalar fields by isosurface extraction it is often difficult to choose isovalues that convey "useful" information. The significance of visualizations using direct volume rendering depends on ..."
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on the choice of good transfer functions. Understanding and using isosurface topology can help in identifying "relevant" isovalues for visualization via isosurfaces and can be used to automatically generate transfer functions. Critical isovalues indicate...
RESEARCH ARTICLE Narrowing Critical Regions and Determining
, 2009
"... One of our primary goals is to help families who have a child with an 18q deletion anticipate medical issues in order to optimize their child’s medical care. To this end we have narrowed the critical regions for four phenotypic features and determined the penetrance for each of those phenotypes when ..."
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One of our primary goals is to help families who have a child with an 18q deletion anticipate medical issues in order to optimize their child’s medical care. To this end we have narrowed the critical regions for four phenotypic features and determined the penetrance for each of those phenotypes
Offline Signature Verification Using Critical Region Matching
- International Journal of Signal Processing, Image Processing and Pattern Recognition
"... Signature can be seen as an individual characteristic of a person which, if modeled with precision can be used for his/her validation. An automated signature verification technique saves valuable time and money. The paper is primarily focused on skilled forgery detection. It emphasizes on the extrac ..."
Abstract
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Cited by 3 (0 self)
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on the extraction of the critical regions which are more prone to mistakes and matches them following a modular graph matching approach. The technique is robust and takes care of the inevitable intra- personal variations. The results show significant improvement over other approaches for detecting skilled forgery
Results 1 - 10
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