Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Stefan Ingi Adalbjörnsson"'
Autor:
Andreas Jakobsson, Christian Jamtheim Gustafsson, Stefan Ingi Adalbjörnsson, Johan Sward, Lars E. Olsson
Publikováno v:
Physics in medicine and biology. 65(22)
Identification of prostate gold fiducial markers in magnetic resonance imaging (MRI) images is challenging when CT images are not available, due to misclassifications from intra-prostatic calcifications. It is also a time consuming task and automated
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::98b986103d2bcaae8fabd8fe333947a9
https://pubmed.ncbi.nlm.nih.gov/33179610
https://pubmed.ncbi.nlm.nih.gov/33179610
Publikováno v:
Signal Processing. 130:105-117
This work treats the estimation of chroma features for harmonic audio signals using a sparse reconstruction framework. Chroma has been used for decades as a key tool in audio analysis, and is typically formed using a periodogram-based approach that m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::56a7fb7b80e93d51d500f4a536ff3ab0
https://doi.org/10.1016/j.sigpro.2016.06.020
https://doi.org/10.1016/j.sigpro.2016.06.020
Publikováno v:
Signal Processing. 128:309-317
In this work, we consider the problem of high-resolution estimation of the parameters detailing an N-dimensional (N-D) signal consisting of an unknown number of exponentially decaying sinusoidal components. Since such signals are not sparse in an ove
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fbb1a23cb4f63ce0a20b6a37b8bd9a15
https://doi.org/10.1016/j.sigpro.2016.04.002
https://doi.org/10.1016/j.sigpro.2016.04.002
Publikováno v:
Signal Processing. 127:56-70
This work treats multi-pitch estimation, and in particular the common misclassification issue wherein the pitch at half the true fundamental frequency, the sub-octave, is chosen instead of the true pitch. Extending on current group LASSO-based method
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fdcafa695ec5cde372859d075780b142
https://doi.org/10.1016/j.sigpro.2016.02.015
https://doi.org/10.1016/j.sigpro.2016.02.015
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing; 24(1), pp 117-129 (2016)
In this paper, we propose a novel method for estimating the locations of near- and/or far-field harmonic audio sources impinging on an arbitrary, but calibrated, sensor array. Using a joint pitch and location estimation formed in two steps, we first
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0bf3f58c9f00d63fcb1eff3260085639
https://doi.org/10.1109/taslp.2015.2497798
https://doi.org/10.1109/taslp.2015.2497798
Publikováno v:
EUSIPCO
We consider the over-fitting problem for multinomial probabilistic Latent Semantic Analysis (pLSA) in collaborative filtering, using a regularization approach. For big data applications, the computational complexity is at a premium and we, therefore,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cd195693ca6dc1f013816d80fdbe35a7
Publikováno v:
EUSIPCO
In this paper, we present a time-recursive implementation of a recent hyperparameter-free group-sparse estimation technique. This is achieved by reformulating the original method, termed group-SPICE, as a square-root group-LASSO with a suitable regul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::268276a20105b4dece5f7629b044eb81
https://doi.org/10.23919/eusipco.2017.8081580
https://doi.org/10.23919/eusipco.2017.8081580
Publikováno v:
ICASSP
In this work, we propose a novel multi-pitch estimation technique that is robust with respect to the inharmonicity commonly occurring in many applications. The method does not require any a priori knowledge of the number of signal sources, the number
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f6527c5e059df4a2cf9c1481398d68a0
https://doi.org/10.1109/icassp.2017.7952172
https://doi.org/10.1109/icassp.2017.7952172
Publikováno v:
ICASSP
In this work, we extend the popular sparse iterative covariance-based estimator (SPICE) by generalizing the formulation to allow for different norm constraint on the signal and noise parameters in the covariance model. For any choice of norms, the re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::73bcac1d1b3327f2db98e97e1325c25e
https://doi.org/10.1109/icassp.2017.7952898
https://doi.org/10.1109/icassp.2017.7952898
Publikováno v:
European Signal Processing Conference (EUSIPCO); CFP1740S-USB, no 1570347373 (2017)
Lund University
Lund University
In this paper, we present a time-recursive implementation of a recent hyperparameter-free group-sparse estimation technique. This is achieved byr eformulating the original method, termed group-SPICE, as a square-root group-LASSO with a suitable regul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::cb3fb28023d1f6ddbdbc54ccea59f23c
https://lup.lub.lu.se/record/40f6dfcc-75fe-4384-931d-d17494c3d55e
https://lup.lub.lu.se/record/40f6dfcc-75fe-4384-931d-d17494c3d55e