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Showing 1 to 20 of 138 for “"random fields"”.

  1. Polarimetry Of Random Fields

    … and spectral scales which are small enough, all fields are fully polarized. In the optical regime, however, instantaneous fields can rarely be examined, and, instead, only average quantities are accessible. The study of polarimetry is concerned with both the description of electromagnetic fields

    ucf

  2. K-differenced vector random fields

    wichita-thes

  3. From random fields to networks

    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1993.

    mit Repository record for From random fields to networks (opens in a new tab)

  4. Gene prediction with conditional random fields

    … thesis, I built upon the semi-Markov conditional random field framework created by DeCaprio et al. to predict protein-coding genes in DNA sequences. Several novel extensions were designed and implemented, including a 29-state model with both semi-Markov and Markov states, an N-best Viterbi …

    mit Repository record for Gene prediction with conditional random fields (opens in a new tab)

  5. Greedy structure learning of Markov Random Fields

    … undirected graphical model, also called a Markov Random Field (MRF), given a set of independent and identically distributed (i.i.d.) samples. Specifically, we introduce an adaptive forward-backward greedy algorithm for learning the structure of a discrete, pairwise MRF given a high dimensional set …

    texas Repository record for Greedy structure learning of Markov Random Fields (opens in a new tab)

  6. Object recognition with latent Conditional Random Fields

    … to local features is modelled by a Conditional Random Field (CRF). We propose an extension of the CRF framework that incorporates hidden variables and combines class conditional CRFs into a unified framework for part-based object recognition. The random field captures spatial coherence between …

    mit Repository record for Object recognition with latent Conditional Random Fields (opens in a new tab)

  7. Optimization of Markov Random Fields in Computer Vision

    … vision tasks can be formulated using Markov Random Fields (MRF). Except in certain special cases, optimizing an MRF is intractable, due to a large number of variables and complex dependencies between them. In this thesis, we present new algorithms to perform inference in MRFs, that are either …

    aus-cath Repository record for Optimization of Markov Random Fields in Computer Vision (opens in a new tab)

  8. Optimization of Markov Random Fields in Computer Vision

    … vision tasks can be formulated using Markov Random Fields (MRF). Except in certain special cases, optimizing an MRF is intractable, due to a large number of variables and complex dependencies between them. In this thesis, we present new algorithms to perform inference in MRFs, that are either …

    anu Repository record for Optimization of Markov Random Fields in Computer Vision (opens in a new tab)

  9. Rational modeling and linear prediction of random fields

    … is proposed that is based upon modeling a random field as the output of a rational linear system driven by the innovations of the field. A variety of linear prediction problems, each depending upon the definition of past, may be formulated for random fields; consequently, there are an equal …

    uiuc Repository record for Rational modeling and linear prediction of random fields (opens in a new tab)

  10. Lossless Coding of Markov Random Fields with Complex Cliques

    The topic of Markov Random Fields (MRFs) has been well studied in the past, and has found practical use in various image processing, and machine learning applications. Where coding is concerned, MRF specific schemes have been largely unexplored. In this thesis, an overview is given of recent …

    queens Repository record for Lossless Coding of Markov Random Fields with Complex Cliques (opens in a new tab)

  11. Spectral densities of discrete and continuous-indexed random fields

    … first looks at sequences of discrete-indexed random fields. When these random fields satisfy certain linear dependence conditions uniformly, each will have a spectral density function (not necessarily continuous) that is bounded between two positive constants. These spectral density functions …

    iu Repository record for Spectral densities of discrete and continuous-indexed random fields (opens in a new tab)

  12. Regularly varying random fields and analyses of extremal clusters

    … the extremes of multivariate regularly varying random fields using the tail field and the spectral field, notions that extend the tail and spectral processes of Basrak and Segers (2009). We discuss several properties and the limit theorems for the related point processes. The spatial context …

    cornell Repository record for Regularly varying random fields and analyses of extremal clusters (opens in a new tab)

  13. Mesoscale random fields of stiffness for in-plane elasticity

    … material properties are not possible for random heterogeneous materials at intermediate length scales, which is to say at some mesoscale above the microscale yet prior to the attainment of the representative volume element (RVE). Focusing on elastic moduli in particular, a micromechanical …

    uiuc Repository record for Mesoscale random fields of stiffness for in-plane elasticity (opens in a new tab)

  14. Evaluation of the difference between two spatiotemporal random fields

    … the spatial characteristics of spatiotemporal random fields is often in demand in various fields of study. Especially in climatology, people are interested in learning the difference between the synthetic climate simulation model and climate field reconstructions (CFR) which are estimates of …

    uiuc Repository record for Evaluation of the difference between two spatiotemporal random fields (opens in a new tab)

  15. SPDE-derived random fields in structural optimisation and elastodynamics

    Random imperfections are an inherent aspect of engineered systems, originating from various sources such as manufacturing variations, material heterogeneity, and environmental factors. These imperfections inevitably introduce uncertainties in the performance of structures which are rarely …

    cambridge Repository record for SPDE-derived random fields in structural optimisation and elastodynamics (opens in a new tab)

  16. Texture modeling--temperature effects on Markov/Gibbs random fields

    Thesis: Sc. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 1991

    mit Repository record for Texture modeling--temperature effects on Markov/Gibbs random fields (opens in a new tab)

  17. Gene identification using phylogenetic metrics with conditional random fields

    … discriminative models such as Conditional Random Fields (CRFs) have recently emerged, which focus specifically on the discrimination problem of gene identification, and can therefore be more powerful. One of the most attractive characteristics of these models is that their general framework …

    mit Repository record for Gene identification using phylogenetic metrics with conditional random fields (opens in a new tab)

  18. Energy-aware Sparse Sensing of Spatial-temporally Correlated Random Fields

    … of energy aware sparse sensing schemes of random fields that are correlated in the space and/or time domains. The objective of sparse sensing is to reduce the number of sensing samples in the space and/or time domains, thus reduce the energy consumption and complexity of the sensing system. …

    arkansas Repository record for Energy-aware Sparse Sensing of Spatial-temporally Correlated Random Fields (opens in a new tab)

  19. Polygonal random fields and the reconstruction of piecewise continuous functions

    Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1993.

    mit Repository record for Polygonal random fields and the reconstruction of piecewise continuous functions (opens in a new tab)

  20. A GPU implementation of tiled belief propagation on Markov random fields

    In this work, we present a parallelized version of tiled belief propagation for stereo matching. The proposed algorithm is implemented in CUDA to leverage parallel processing capabilities of GPUs. In our solution, the original tiled BP algorithm is combined with a number of optimizations specific …

    uiuc Repository record for A GPU implementation of tiled belief propagation on Markov random fields (opens in a new tab)

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