• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations

Tools

Sorted by:
Try your query at:
Semantic Scholar Scholar Academic
Google Bing DBLP
Results 1 - 10 of 60,182
Next 10 →

A modular three-dimensional finite-difference ground-water flow model

by Model (michael Mcdonald, Arlen Harbaugh - U.S. Geological Survey Techniques of WaterResources Investigations Book 6, Chapter A1 , 1988
"... The primary objective of this course is to discuss the principals of finite difference methods and their applications in groundwater modeling. The emphasis of the class lectures is on the theoretical aspects of numerical modeling (finite difference method). Steps involved in simulation of groundwate ..."
Abstract - Cited by 508 (5 self) - Add to MetaCart
of groundwater systems under various initial/boundary conditions and management schemes will be practiced. The emphasis of the student presentations will be based on published papers concerning the applied aspects of groundwater computer modeling utilizing finite difference and analytical computer models

Three-dimensional object recognition from single two-dimensional images

by David G. Lowe - Artificial Intelligence , 1987
"... A computer vision system has been implemented that can recognize threedimensional objects from unknown viewpoints in single gray-scale images. Unlike most other approaches, the recognition is accomplished without any attempt to reconstruct depth information bottom-up from the visual input. Instead, ..."
Abstract - Cited by 484 (7 self) - Add to MetaCart
, three other mechanisms are used that can bridge the gap between the two-dimensional image and knowledge of three-dimensional objects. First, a process of perceptual organization is used to form groupings and structures in the image that are likely to be invariant over a wide range of viewpoints. Second

Learning to predict by the methods of temporal differences

by Richard S. Sutton - MACHINE LEARNING , 1988
"... This article introduces a class of incremental learning procedures specialized for prediction – that is, for using past experience with an incompletely known system to predict its future behavior. Whereas conventional prediction-learning methods assign credit by means of the difference between predi ..."
Abstract - Cited by 1521 (56 self) - Add to MetaCart
, they have remained poorly understood. Here we prove their convergence and optimality for special cases and relate them to supervised-learning methods. For most real-world prediction problems, temporal-difference methods require less memory and less peak computation than conventional methods and they produce

Atmospheric Modeling, Data Assimilation and Predictability

by Eugenia Kalnay , 2003
"... Numerical weather prediction (NWP) now provides major guidance in our daily weather forecast. The accuracy of NWP models has improved steadily since the first successful experiment made by Charney, Fj!rtoft and von Neuman (1950). During the past 50 years, a large number of technical papers and repor ..."
Abstract - Cited by 626 (33 self) - Add to MetaCart
of data assimilation and predictability. It incorporates all aspects of environmental computer modeling including an historical overview of NWP, equations of motion and their approximations, a modern description of the methods to determine the initial conditions using weather observations and a clear

Prediction of complete gene structures in human genomic DNA

by Chris Burge, Samuel Karlin - J. Mol. Biol , 1997
"... The problem of identifying genes in genomic DNA sequences by computational methods has attracted considerable research attention in recent years. From one point of view, the problem is closely ..."
Abstract - Cited by 1177 (9 self) - Add to MetaCart
The problem of identifying genes in genomic DNA sequences by computational methods has attracted considerable research attention in recent years. From one point of view, the problem is closely

Hidden Markov models in computational biology: applications to protein modeling

by Anders Krogh, Michael Brown, I. Saira Mian, Kimmen Sjölander, David Haussler - JOURNAL OF MOLECULAR BIOLOGY , 1994
"... Hidden.Markov Models (HMMs) are applied t.0 the problems of statistical modeling, database searching and multiple sequence alignment of protein families and protein domains. These methods are demonstrated the on globin family, the protein kinase catalytic domain, and the EF-hand calcium binding moti ..."
Abstract - Cited by 655 (39 self) - Add to MetaCart
protein family, or contain the given domain. The Hi " produces multiple alignments of good quality that agree closely with the alignments produced by programs that incorporate three-dimensional structural information. When employed in discrimination tests (by examining how closely the sequences in a

Predicting Internet Network Distance with Coordinates-Based Approaches

by T. S. Eugene Ng, Hui Zhang - In INFOCOM , 2001
"... In this paper, we propose to use coordinates-based mechanisms in a peer-to-peer architecture to predict Internet network distance (i.e. round-trip propagation and transmission delay) . We study two mechanisms. The first is a previously proposed scheme, called the triangulated heuristic, which is bas ..."
Abstract - Cited by 631 (6 self) - Add to MetaCart
In this paper, we propose to use coordinates-based mechanisms in a peer-to-peer architecture to predict Internet network distance (i.e. round-trip propagation and transmission delay) . We study two mechanisms. The first is a previously proposed scheme, called the triangulated heuristic, which

Identification of Prokaryotic and Eukaryotic Signal Peptides and Prediction of Their Cleavage Sites

by Henrik Nielsen, Jacob Engelbrecht, Søren Brunak, Gunnar von Heijne , 1997
"... We have developed a new method for identification of signal peptides and their cleavage sites based on neural networks trained on separate sets of prokaryotic and eukaryotic sequences. The method performs significantly better than previous prediction schemes, and can easily be applied on genome-wide ..."
Abstract - Cited by 787 (17 self) - Add to MetaCart
-wide data sets. Discrimination between cleaved signal peptides and uncleaved N-terminal signal-anchor sequences is also possible, thoughwith lower precision. Predictions can be made on a publicly available WWW server. Present address: Novo Nordisk A/S, Scientific Computing, Building 9M1, Novo Alle, DK

A study of branch prediction strategies

by E. Smith, Arden Hills Minnesota - In Proceedings of the 8th annual symposium on Computer Architecture
"... In high-performance computer systems. performance losses due to conditional branch instructrons can be minrmized by predicting a branch outcome and fetching, decoding, and/or issuing subsequent instructions before the actual outcome is known. This paper discusses branch prediction strategies wrth th ..."
Abstract - Cited by 481 (16 self) - Add to MetaCart
In high-performance computer systems. performance losses due to conditional branch instructrons can be minrmized by predicting a branch outcome and fetching, decoding, and/or issuing subsequent instructions before the actual outcome is known. This paper discusses branch prediction strategies wrth

The quadtree and related hierarchical data structures

by Hanan Samet - ACM Computing Surveys , 1984
"... A tutorial survey is presented of the quadtree and related hierarchical data structures. They are based on the principle of recursive decomposition. The emphasis is on the representation of data used in applications in image processing, computer graphics, geographic information systems, and robotics ..."
Abstract - Cited by 541 (12 self) - Add to MetaCart
, and robotics. There is a greater emphasis on region data (i.e., two-dimensional shapes) and to a lesser extent on point, curvilinear, and threedimensional data. A number of operations in which such data structures find use are examined in greater detail.
Next 10 →
Results 1 - 10 of 60,182
Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University