Results 1 - 10 of 90,622

Construction of abstract state graphs with PVS

by Susanne Graf, Hassen Saidi , 1997
"... We describe in this paper a method based on abstract interpretation which, from a theoretical point of view, is similar to the splitting methods proposed in [DGG93, Dam96] but the weaker abstract transition relation we use, allows us to construct automatically abstract state graphs paying a reasonab ..."
Abstract - Cited by 742 (10 self) - Add to MetaCart
reasonable price. We consider a particular set of abstract states: the set of the monomials on a set of state predicates ' 1 ; :::; ' ` . The successor of an abstract state m for a transition ø of the program is the least monomial satisfied by all successors via ø of concrete states satisfying m

GPS-Less Low Cost Outdoor Localization for Very Small Devices.

by Nirupama Bulusu , John Heidemann , Deborah Estrin - IEEE Personal Communications Magazine, , 2000
"... Abstract-Instrumenting the physical world through large networks of wireless sensor nodes, particularly for applications like environmental monitoring of water and soil, requires that these nodes be very small, light, untethered and unobtrusive. The problem of localization, i.e., determining where ..."
Abstract - Cited by 1000 (27 self) - Add to MetaCart
Abstract-Instrumenting the physical world through large networks of wireless sensor nodes, particularly for applications like environmental monitoring of water and soil, requires that these nodes be very small, light, untethered and unobtrusive. The problem of localization, i.e., determining where

Basic objects in natural categories

by Eleanor Rosch, Carolyn B. Mervis, Wayne D. Gray, David M. Johnson, Penny Boyes-braem - COGNITIVE PSYCHOLOGY , 1976
"... Categorizations which humans make of the concrete world are not arbitrary but highly determined. In taxonomies of concrete objects, there is one level of abstraction at which the most basic category cuts are made. Basic categories are those which carry the most information, possess the highest categ ..."
Abstract - Cited by 892 (1 self) - Add to MetaCart
Categorizations which humans make of the concrete world are not arbitrary but highly determined. In taxonomies of concrete objects, there is one level of abstraction at which the most basic category cuts are made. Basic categories are those which carry the most information, possess the highest

Feature selection: Evaluation, application, and small sample performance

by Anil Jain, Douglas Zongker - IEEE Transactions on Pattern Analysis and Machine Intelligence , 1997
"... Abstract—A large number of algorithms have been proposed for feature subset selection. Our experimental results show that the sequential forward floating selection (SFFS) algorithm, proposed by Pudil et al., dominates the other algorithms tested. We study the problem of choosing an optimal feature s ..."
Abstract - Cited by 474 (13 self) - Add to MetaCart
Abstract—A large number of algorithms have been proposed for feature subset selection. Our experimental results show that the sequential forward floating selection (SFFS) algorithm, proposed by Pudil et al., dominates the other algorithms tested. We study the problem of choosing an optimal feature

SELF: The power of simplicity

by David Ungar, Randall B. Smith , 1991
"... SELF is an object-oriented language for exploratory programming based on a small number of simple and concrete ideas: prototypes, slots, and behavior. Prototypes combine inheritance and instantiation to provide a framework that is simpler and more flexible than most object-oriented languages. Slots ..."
Abstract - Cited by 640 (19 self) - Add to MetaCart
SELF is an object-oriented language for exploratory programming based on a small number of simple and concrete ideas: prototypes, slots, and behavior. Prototypes combine inheritance and instantiation to provide a framework that is simpler and more flexible than most object-oriented languages

Illiquidity and stock returns: cross-section and time-series effects,

by Yakov Amihud - Journal of Financial Markets , 2002
"... Abstract This paper shows that over time, expected market illiquidity positively affects ex ante stock excess return, suggesting that expected stock excess return partly represents an illiquidity premium. This complements the cross-sectional positive return-illiquidity relationship. Also, stock ret ..."
Abstract - Cited by 864 (9 self) - Add to MetaCart
Abstract This paper shows that over time, expected market illiquidity positively affects ex ante stock excess return, suggesting that expected stock excess return partly represents an illiquidity premium. This complements the cross-sectional positive return-illiquidity relationship. Also, stock

Local grayvalue invariants for image retrieval

by Cordelia Schmid, Roger Mohr - IEEE Transactions on Pattern Analysis and Machine Intelligence , 1997
"... Abstract—This paper addresses the problem of retrieving images from large image databases. The method is based on local grayvalue invariants which are computed at automatically detected interest points. A voting algorithm and semilocal constraints make retrieval possible. Indexing allows for efficie ..."
Abstract - Cited by 548 (27 self) - Add to MetaCart
Abstract—This paper addresses the problem of retrieving images from large image databases. The method is based on local grayvalue invariants which are computed at automatically detected interest points. A voting algorithm and semilocal constraints make retrieval possible. Indexing allows

Learning generative visual models from few training examples: an incremental Bayesian approach tested on 101 object categories

by Li Fei-fei , 2004
"... Abstract — Current computational approaches to learning visual object categories require thousands of training images, are slow, cannot learn in an incremental manner and cannot incorporate prior information into the learning process. In addition, no algorithm presented in the literature has been te ..."
Abstract - Cited by 784 (16 self) - Add to MetaCart
Abstract — Current computational approaches to learning visual object categories require thousands of training images, are slow, cannot learn in an incremental manner and cannot incorporate prior information into the learning process. In addition, no algorithm presented in the literature has been

Linear models and empirical bayes methods for assessing differential expression in microarray experiments.

by Gordon K Smyth , Gordon K Smyth - Stat. Appl. Genet. Mol. Biol. , 2004
"... Abstract The problem of identifying differentially expressed genes in designed microarray experiments is considered. Lonnstedt and Speed (2002) derived an expression for the posterior odds of differential expression in a replicated two-color experiment using a simple hierarchical parametric model. ..."
Abstract - Cited by 1321 (24 self) - Add to MetaCart
Abstract The problem of identifying differentially expressed genes in designed microarray experiments is considered. Lonnstedt and Speed (2002) derived an expression for the posterior odds of differential expression in a replicated two-color experiment using a simple hierarchical parametric model

Nonparametric model for background subtraction

by Ahmed Elgammal, David Harwood, Larry Davis - in ECCV ’00 , 2000
"... Abstract. Background subtraction is a method typically used to seg-ment moving regions in image sequences taken from a static camera by comparing each new frame to a model of the scene background. We present a novel non-parametric background model and a background subtraction approach. The model can ..."
Abstract - Cited by 545 (17 self) - Add to MetaCart
Abstract. Background subtraction is a method typically used to seg-ment moving regions in image sequences taken from a static camera by comparing each new frame to a model of the scene background. We present a novel non-parametric background model and a background subtraction approach. The model
Results 1 - 10 of 90,622