Zobrazeno 1 - 10
of 188
pro vyhledávání: '"Ulf Grenander"'
Autor:
Ulf Grenander
This monograph reports a thought experiment with a mathematical structure intended to illustrate the workings of a mind. It presents a mathematical theory of human thought based on pattern theory with a graph-based approach to thinking. The method il
Autor:
Ulf Grenander, Michael I. Miller
Pattern Theory: From Representation to Inference provides a comprehensive and accessible overview of the modern challenges in signal, data and pattern analysis in speech recognition, computational linguistics, image analysis and computer vision. Aime
Publikováno v:
Quarterly of Applied Mathematics. 69:227-260
In computational anatomy large deformations of anatomical structures observed in images are represented by diffeomorphic flows on the background space of coordinates. They are usually maximum a posteriori (MAP) estimates obtained by minimization of t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aa80aa5f5d59c1f20aad42b69779c819
https://doi.org/10.1090/s0033-569x-2011-01192-4
https://doi.org/10.1090/s0033-569x-2011-01192-4
Autor:
Ulf Grenander
Publikováno v:
Quarterly of Applied Mathematics. 65:205-257
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8ceccba9ebe2caa9b0e7eeb392b607ac
https://doi.org/10.1090/s0033-569x-07-01028-8
https://doi.org/10.1090/s0033-569x-07-01028-8
Publikováno v:
IEEE Transactions on Medical Imaging. 26:648-659
Mathematical and statistical modeling of biological growth is an important problem in medical diagnostics. Here, we seek tools to analyze changes in anatomical parts using images collected over time. We introduce a structured model, called Growth by
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c18f39c8735525aa1833a7f361b0dc66
https://doi.org/10.1109/tmi.2006.891500
https://doi.org/10.1109/tmi.2006.891500
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 24:1200-1214
Seeking probability models for images, we employ a spectral approach where the images are decomposed using bandpass filters and probability models are imposed on the filter outputs (also called spectral components). We employ a (two-parameter) family
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::62276707fd987361bbcb9c1b0eea55a8
https://doi.org/10.1109/tpami.2002.1033212
https://doi.org/10.1109/tpami.2002.1033212
Publikováno v:
Journal of Statistical Planning and Inference. 103:15-37
In the problem of recognizing targets from their observed images, the estimation of target orientations, as elements of the rotation group SO(3), plays an important role. For k-objects the unknown parameter is an element of SO(3) k . Since k may be u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7b4bf82c43b2c772ed671e538f289e5b
https://doi.org/10.1016/s0378-3758(01)00195-1
https://doi.org/10.1016/s0378-3758(01)00195-1
Autor:
Anuj Srivastava, Ulf Grenander
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 23:424-429
We propose a framework for modeling clutter in natural images. Assuming that: 1) images are made up of 2D (projected) views of 3D (real) objects and 2) certain simplifying conditions hold, we derive an analytical density for natural images. This expr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ada1f2de6220d3b9b7ce4c42a69198d4
https://doi.org/10.1109/34.917579
https://doi.org/10.1109/34.917579
Publikováno v:
IEEE Transactions on Information Theory. 46:1658-1665
This article investigates the asymptotic performance of Bayesian target recognition algorithms using deformable-template representations. Rigid computer-aided design (CAD) models represent the underlying targets; low-dimensional matrix Lie-groups (ro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::73ee22a3aede1f21d0a2afa935110ec2
https://doi.org/10.1109/18.850712
https://doi.org/10.1109/18.850712
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 22:337-347
Asymptotic approximations to the partition function of Gaussian random fields are derived. Textures are characterized via Gaussian random fields induced by stochastic difference equations determined by finitely supported, stationary, linear differenc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::972b01cdfeb41613d3b15145d8accb42
https://doi.org/10.1109/34.845376
https://doi.org/10.1109/34.845376