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A reservoir-driven non-stationary hidden Markov model
2012
Pattern Recognition
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In this work, we propose a novel approach towards sequential data modeling that leverages the strengths of hidden Markov models and echo-state networks (ESNs) in the context of nonparametric Bayesian inference ...
We derive an efficient inference algorithm for our model under the variational Bayesian paradigm, and we examine the efficacy of our approach considering a number of sequential data modeling applications ...
Rabiner, A tutorial on hidden Markov models and selected applications in speech recognition, Proceedings of the IEEE 77 (1989) 245-255. [2] O. Cappé, E. Moulines, T. ...
doi:10.1016/j.patcog.2012.04.018
fatcat:kxcr3rpx6bezvbyw7dcnr4p6ga
Bayesian Logistic Shape Model Inference: application to cochlea image segmentation
[article]
2021
arXiv
pre-print
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This framework is applied to the segmentation of cochlea structures from clinical CT images constrained by a 10 parameter shape model. ...
The proposed framework defines a likelihood appearance probability and a prior label probability based on a generic shape function through a logistic function. ...
This framework is applied to the problem of cochlea segmentation on CT images based on a parametric shape model with 10 parameters, and an imaging model defined as a mixture of Student's t-distributions ...
arXiv:2105.02045v1
fatcat:neywcftcqrhnbc33673ukpezfe
The Infinite-Order Conditional Random Field Model for Sequential Data Modeling
2013
IEEE Transactions on Pattern Analysis and Machine Intelligence
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To resolve these issues, in this paper we introduce a novel CRF formulation, based on the postulation of an energy function which entails infinitely-long time-dependencies between the modeled data. ...
Building blocks of our novel approach are: (i) the sequence memoizer, a recently proposed nonparametric Bayesian approach for modeling label sequences with infinitely-long time dependencies; and (b) a ...
CONCLUSIONS In this paper, we presented a novel formulation of linearchain CRF models, based on the postulation of an energy function which entails infinitely-long time-dependencies between the modeled ...
doi:10.1109/tpami.2012.208
pmid:23599063
fatcat:x5yg4fqn4zeqholeybhoginbby
Robust density modelling using the student's t-distribution for human action recognition
2011
2011 18th IEEE International Conference on Image Processing
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In this paper, we present an HMM which uses mixtures of t-distributions as observation probabilities and show how experiments over two well-known datasets (Weizmann, MuHAVi) reported a remarkable improvement ...
In this paper, we present an HMM which uses mixtures of t-distributions as observation probabilities and show how experiments over two well-known datasets (Weizmann, MuHAVi) reported a remarkable improvement ...
THE STUDENT'S t-DISTRIBUTION The Student's t-distribution could be considered as an infinite mixture of scaled Gaussians with the same mean but variable variance (or covariance) produced by a prior Gamma ...
doi:10.1109/icip.2011.6116366
dblp:conf/icip/MoghaddamP11
fatcat:2tpknyor7fenpkmjdjhbvhfski
A review of uncertainty quantification in deep learning: Techniques, applications and challenges
2021
Information Fusion
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(e.g., image restoration), medical image analysis (e.g., medical image classification and segmentation), natural language processing (e.g., text classification, social media texts and recidivism risk-scoring ...
In this regard, researchers have proposed different UQ methods and examined their performance in a variety of applications such as computer vision (e.g., selfdriving cars and object detection), image processing ...
Based on these findings, a novel model (called Fig. 4 . A graphical representation of several visualizations of variational distributions on a simple NN. ...
doi:10.1016/j.inffus.2021.05.008
fatcat:yschhguyxbfntftj6jv4dgywxm
ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI
2017
Medical Image Analysis
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Ischemic stroke is the most common cerebrovascular disease, and its diagnosis, treatment, and study relies on non-invasive imaging. ...
A total of 16 research groups participated with a wide range of state-ofthe-art automatic segmentation algorithms. ...
The other methods in order of decreasing rank are: another RF method, a modeling approach, a rule based approach, another modeling approach, and a CNN. ...
doi:10.1016/j.media.2016.07.009
pmid:27475911
pmcid:PMC5099118
fatcat:mmmolbl4dzbbzibtjh7nmot6hm
2021 Index IEEE Transactions on Signal Processing Vol. 69
2021
IEEE Transactions on Signal Processing
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., +, TSP 2021 5463-5478 Filtering in Pairwise Markov Model With Student's t Non-Stationary Noise With Application to Target Tracking. ...
Romero, D., +, TSP 2021 150-164 Filtering in Pairwise Markov Model With Student's t Non-Stationary Noise With Application to Target Tracking. ...
On Unlimited Sampling and Reconstruction. 3827-3839
Integer programming Generalized Non-Redundant Sparse Array Designs. ...
doi:10.1109/tsp.2022.3162899
fatcat:kcubj566gzb4zkj7xb5r5we3ri
Robust Model-Based Learning to Discover New Wheat Varieties and Discriminate Adulterated Kernels in X-Ray Images
[chapter]
2021
Studies in Classification, Data Analysis, and Knowledge Organization
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of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission ...
Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. ...
Acknowledgements The authors thank two anonymous referees for their valuable comments on the original version of the manuscript. ...
doi:10.1007/978-3-030-69944-4_4
fatcat:e5bfknks2vcwpc5mhyzp2vvsfq
Automatic Target Recognition on Synthetic Aperture Radar Imagery: A Survey
[article]
2020
arXiv
pre-print
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Based on the current methodology trends, we propose a taxonomy for the SAR ATR architectures, along with a direct comparison of the strengths and weaknesses of each method under both standard and extended ...
Automatic Target Recognition (ATR) for military applications is one of the core processes towards enhancing intelligencer and autonomously operating military platforms. ...
For the SRC module, a novel adaptive elastic net type of optimization is proposed that balances the advantages of 1 l norm − and 2 l norm − depending on a Gaussian Mixture Model (GMM) [139] analysis ...
arXiv:2007.02106v2
fatcat:qz3kfu5varasjkagj44pw5byei
Effective CRISPR/Cas9-based nucleotide editing in zebrafish to model human genetic cardiovascular disorders
2018
Disease Models & Mechanisms
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So far, most studies have relied on broad overexpression of transgenes harboring patient-derived mutations or loss-of-function mutants, which incompletely model the human disease allele in terms of expression ...
The zebrafish (Danio rerio) has become a popular vertebrate model organism to study organ formation and function due to its optical clarity and rapid embryonic development. ...
In conclusion, we have improved a CRISPR/Cas9-based singlenucleotide-editing approach with which we established novel zebrafish KI lines that closely model cardiovascular features of human disease. ...
doi:10.1242/dmm.035469
fatcat:om67lptes5esbiw3hociwvymym
Augmented CycleGANs for Continuous Scale Normal-to-Lombard Speaking Style Conversion
2019
Interspeech 2019
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If a non-parametric prior distribution is used, the theoretically infinite number of components K is truncated to a truncation limit T for practical computations (Blei and Jordan, 2006) . ...
on the type of unvoiced segment they model. ...
doi:10.21437/interspeech.2019-1681
dblp:conf/interspeech/SeshadriJAR19
fatcat:tfobvlkjv5dvdeaxvzby3mb2y4
2020 Index IEEE Transactions on Industrial Informatics Vol. 16
2020
IEEE Transactions on Industrial Informatics
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Forests-Based Model for Ultra-Short-Term Prediction of PV Characteristics; TII Jan. 2020 202-214 Imran, A., see Hussain, B., TII Aug. 2020 4986-4996 Imran, M., see Fu, S., TII Sept. 2020 6013-6022 ...
on Intelligent Clustering in Local Area Industrial IoT Systems; TII June 2020 3697-3707 Jia, S., see Chen, C., 1873-1884 Jia, W., see Wang, T., 2054-2062 Jia, W., see Lian, J., 1343-1351 Jia, W., see ...
., +, TII April 2020 2413-2422 Semisupervised Robust Modeling of Multimode Industrial Processes for Quality Variable Prediction Based on Student's t Mixture Model. ...
doi:10.1109/tii.2021.3053362
fatcat:blfvdtsc3fdstnk6qoaazskd3i
Comprehensive Exploration of Synthetic Data Generation: A Survey
[article]
2024
arXiv
pre-print
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2024 pre-print arXiv:2401.02524v1 fatcat:kbds54lxcnajbjm7ibglqidt6a
The findings reveal increased model performance and complexity, with neural network-based approaches prevailing, except for privacy-preserving data generation. ...
This work serves as a guide for SDG model selection and identifies crucial areas for future exploration. ...
The novel approach includes integrating an autoencoder with the generator and implementing two distance constraints, one in the latent space and another based on discriminator scores. ...
arXiv:2401.02524v2
fatcat:si2v4ayavbav5pi3a5nw33keme
Advances in Electron Microscopy with Deep Learning
2020
Zenodo
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Highlights include a comprehensive review of deep learning in electron microscopy; large new electron microscopy datasets for machine learning, dataset search engines based on variational autoencoders, ...
and automatic data clustering by t-distributed stochastic neighbour embedding; adaptive learning rate clipping to stabilize learning; generative adversarial networks for compressed sensing with spiral ...
In addition, part of the text in section 1.2 is adapted from our earlier work with permission 201 under a Creative Commons Attribution 4.0 73 license. ...
doi:10.5281/zenodo.4598227
fatcat:hm2ksetmsvf37adjjefmmbakvq
Advances in Electron Microscopy with Deep Learning
2020
Zenodo
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Highlights include a comprehensive review of deep learning in electron microscopy; large new electron microscopy datasets for machine learning, dataset search engines based on variational autoencoders, ...
and automatic data clustering by t-distributed stochastic neighbour embedding; adaptive learning rate clipping to stabilize learning; generative adversarial networks for compressed sensing with spiral ...
In addition, part of the text in section 1.2 is adapted from our earlier work with permission 201 under a Creative Commons Attribution 4.0 73 license. ...
doi:10.5281/zenodo.4591029
fatcat:zn2hvfyupvdwlnvsscdgswayci
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