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Discovering Modes of an Image Population through Mixture Modeling
[chapter]
2008
Lecture Notes in Computer Science
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The algorithm produced three modes that mainly corresponded to a sub-population of healthy controls, a sub-population of patients with dementia and a mixture group that contained both types. ...
These results suggest that the algorithm can be used to discover sub-populations that correspond to interesting structural or functional "modes." ...
These results suggest that iCluster can be used to probe a population of images to discover important structural or functional "modes." ...
doi:10.1007/978-3-540-85990-1_46
fatcat:c2qvvhlwn5hanmkr73l6z42bmq
Discovering modes of an image population through mixture modeling
2008
Preserved Fulltext
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The algorithm produced three modes that mainly corresponded to a sub-population of healthy controls, a sub-population of patients with dementia and a mixture group that contained both types. ...
These results suggest that the algorithm can be used to discover sub-populations that correspond to interesting structural or functional "modes". ...
These results suggest that iCluster can be used to probe a population of images to discover important structural or functional "modes." ...
pmid:18982628
pmcid:PMC2671151
fatcat:5zsrhh4zabfx3mcigltzf6mxmy
Image-driven population analysis through mixture modeling
2009
2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro
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We derive the algorithm based on a generative model of an image population as a mixture of deformable template images. We validate and explore our method in four experiments. ...
The output of the algorithm is a small number of template images that represent different modes in a population. ...
Support for this research is provided in part by the Department of Veterans Affairs Merit Awards, National Alliance for Medical Image Analysis (NIH NIBIB NAMIC U54-EB005149), the Neuroimaging Analysis ...
doi:10.1109/isbi.2009.5193178
dblp:conf/isbi/Sabuncu09
fatcat:ldgun3bxtfcpfjpjxfbzdekzti
Image-Driven Population Analysis Through Mixture Modeling
2009
IEEE Transactions on Medical Imaging
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We derive the algorithm based on a generative model of an image population as a mixture of deformable template images. We validate and explore our method in four experiments. ...
The output of the algorithm is a small number of template images that represent different modes in a population. ...
Support for this research is provided in part by the Department of Veterans Affairs Merit Awards, National Alliance for Medical Image Analysis (NIH NIBIB NAMIC U54-EB005149), the Neuroimaging Analysis ...
doi:10.1109/tmi.2009.2017942
pmid:19336293
pmcid:PMC2832589
fatcat:m42yn2u24jezrjzr46ejgqjfl4
Fashion Style Generation: Evolutionary Search with Gaussian Mixture Models in the Latent Space
[article]
2022
arXiv
pre-print
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Over generations, a genetic algorithm optimizes a population of designs to increase their probability of belonging to one of the Gaussian mixture components or styles. ...
A Gaussian mixture model is applied to identify fashion styles based on the higher-layer representations of outfits in a clothing-specific attribute prediction model. ...
Clustering models such as a Gaussian mixture model (GMM) have previously been applied to find recurring components in the attribute embedding of images [22, 1] . ...
arXiv:2204.00592v2
fatcat:bmoxmyzseva4jperyii3eegrve
Mixture of Probabilistic Principal Component Analyzers for Shapes from Point Sets
2018
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Statistics are often limited to the variations around a single population mean, not necessarily representing any of the shape subpopulations, with an arbitrary number of variation modes. ...
models for each population. ...
In 2014, he was awarded an IIF Marie-Curie Fellowship for statistical modeling of morphology and function from population in University of Sheffield, where he recently works as a Lecturer in Medical image ...
doi:10.1109/tpami.2017.2700276
pmid:28475045
fatcat:gdnf5gii35fjxcv2l6e2enekge
Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations
2008
BMC Bioinformatics
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The Bayesian modelling methods introduced in this article represent an array of enhanced tools for learning the genetic structure of populations. ...
With these methods it is possible, e.g., to fit genetic mixture models using user-specified numbers of clusters and to estimate levels of admixture under a genetic linkage model. ...
Acknowledgements This work was supported by the Academy of Finland, grant no. 121301 and by the ComBi and ComMIT graduate schools. ...
doi:10.1186/1471-2105-9-539
pmid:19087322
pmcid:PMC2629778
fatcat:7s5crgixjnedth7w3w5vyq66t4
Fungicide resistance: facing the challenge – a review
2016
Plant Protection Science
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pathogen populations in field crops. ...
Experience amassed over the past fifty years has emphasised the importance of diversity in modes of action in anti-resistance strategies. ...
Both modelling and experimental evidence from many studies show that mixtures do indeed slow the evolution to an at risk partner (Brent & Hollomon 2007b; van den Bosch et al. 2014) . ...
doi:10.17221/42/2015-pps
fatcat:ntncwxav3zgkdk3vugxw7umyji
Evolutionary Generative Adversarial Networks
[article]
2018
arXiv
pre-print
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In this way, E-GAN overcomes the limitations of an individual adversarial training objective and always preserves the best offspring, contributing to progress in and the success of GANs. ...
We also utilize an evaluation mechanism to measure the quality and diversity of generated samples, such that only well-performing generator(s) are preserved and used for further training. ...
architectures through an evolutionary search [35, 20, 25] . ...
arXiv:1803.00657v1
fatcat:ngoz424hcrhtxc4yddyhw4sx2e
Evidence for Two Hot-Jupiter Formation Paths
2017
Astronomical Journal
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2017 pre-print arXiv:1703.09711v1 fatcat:5so27infwfedrigvcfonxgkage
channels, and applying a hierarchical Bayesian mixture model of truncated power laws of the form x^γ-1 to constrain the population-level parameters of interest (e.g., location of inner edges, γ, mixture ...
We approach this problem using data from several exoplanet surveys (radial velocity, Kepler, HAT, and WASP) allowing for either a single population or a mixture of populations associated with these formation ...
γ 2 power law index for second mixture component in x f i ith mixture component fraction pare to the observations (e.g., through planet population synthesis models), we approach this problem from a data-driven ...
doi:10.3847/1538-3881/aa82b3
fatcat:ommfvclfqbhixcqlylw4xvclly
Demonstrating the Evolution of GANs through t-SNE
[article]
2021
arXiv
pre-print
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Generative Adversarial Networks (GANs) are powerful generative models that achieved strong results, mainly in the image domain. ...
The results show both by visual inspection and metrics that the Evolutionary Algorithm gradually improves discriminators and generators through generations, avoiding problems such as mode collapse. ...
Acknowledgments This work is partially funded by the project grant DSAIPA/DS/0022/2018 (GADgET), by national funds through the FCT -Foundation for Science and ...
arXiv:2102.00524v2
fatcat:zgjy5stdxnhtbnbmkjmssgyfw4
A Faint Halo Star Cluster Discovered in the Blanco Imaging of the Southern Sky Survey
2019
Astrophysical Journal
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2018 pre-print arXiv:1812.06318v1 fatcat:sorn4pcltba3navzkjqc4cvatiOther Versions
We present the discovery of a faint, resolved stellar system, BLISS J0321+0438 (BLISS 1), found in Dark Energy Camera data from the first observing run of the Blanco Imaging of the Southern Sky (BLISS) ...
Combining the available positional and velocity information with simulations of the accreted satellite population of the Large Magellanic Cloud, we find that it is unlikely that BLISS J0321+0438 (BLISS ...
We estimate the proper motion of BLISS J0321+0438 (BLISS 1) using the Gaussian mixture model analysis described in Section 2.2 of Pace & Li (2018) . ...
doi:10.3847/1538-4357/ab0bb8
fatcat:bcoj3ffvqzeixlfwje6roo2a7y
DynaMorph: learning morphodynamic states of human cells with live imaging and sc-RNAseq
[article]
2020
bioRxiv
pre-print
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Morphological states of human cells are widely imaged and analyzed to diagnose diseases and to discover biological mechanisms. ...
We propose a computational framework, DynaMorph, that combines quantitative label-free imaging and deep learning for automated discovery of morphodynamic states. ...
We thank Greg Huber for discussions around the physical models of cell states. ...
doi:10.1101/2020.07.20.213074
fatcat:yw3fdjiwdrhhpca6b6i63btshe
Bayesian Nonparametrics for Non-exhaustive Learning
[article]
2019
arXiv
pre-print
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problem, which is at the root of many recently discovered limitations of deep learning. ...
The presented study which has been motivated by two important applications proposes a NEL algorithm built on a highly flexible, doubly non-parametric Bayesian Gaussian mixture model that can grow arbitrarily ...
Experiments with Simulated Data We use a two layer Gaussian mixture model similar to I 2 GMM to generate a 2D simulated data with multi-mode class distributions. ...
arXiv:1908.09736v1
fatcat:kvdp2uhnknhgvj2co4qpvg6g4q
Visible and near-infrared spectroscopy of the Centaur 32532 (2001 PT$_{\mathsf {13}}$)
2002
Astronomy and Astrophysics
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) within the framework of an ESO large program on the Trans-Neptunian objects (TNOs) and Centaurs. ...
In one spectrum there is the possible presence of signatures of water ice in small amounts. Two models have been proposed to interpret the surface composition of this Centaur. ...
The aim is to provide photometric and spectroscopic data in the visible and near-infrared ranges for a large set of objects to study the physical properties and composition of this newly discovered population ...
doi:10.1051/0004-6361:20021186
fatcat:xykrfrsuibcxll5re4jy3w52o4
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