These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
5. Regularized mixture density estimation with an analytical setting of shrinkage intensities. Halbe Z; Bortman M; Aladjem M IEEE Trans Neural Netw Learn Syst; 2013 Mar; 24(3):460-70. PubMed ID: 24808318 [TBL] [Abstract][Full Text] [Related]
6. A Nonsymmetric Mixture Model for Unsupervised Image Segmentation. Nguyen TM; Wu QM IEEE Trans Cybern; 2013 Apr; 43(2):751-65. PubMed ID: 22987532 [TBL] [Abstract][Full Text] [Related]
7. Bayesian pixel classification using spatially variant finite mixtures and the generalized EM algorithm. Sanjay-Gopal S; Hebert TJ IEEE Trans Image Process; 1998; 7(7):1014-28. PubMed ID: 18276317 [TBL] [Abstract][Full Text] [Related]
8. Attraction-repulsion expectation-maximization algorithm for image reconstruction and sensor field estimation. Hong H; Schonfeld D IEEE Trans Image Process; 2009 Sep; 18(9):2004-11. PubMed ID: 19502130 [TBL] [Abstract][Full Text] [Related]
9. A transformation-based approach to Gaussian mixture density estimation for bounded data. Scrucca L Biom J; 2019 Jul; 61(4):873-888. PubMed ID: 30983031 [TBL] [Abstract][Full Text] [Related]
10. A parsimonious mixture of Gaussian trees model for oversampling in imbalanced and multimodal time-series classification. Cao H; Tan VY; Pang JZ IEEE Trans Neural Netw Learn Syst; 2014 Dec; 25(12):2226-39. PubMed ID: 25420245 [TBL] [Abstract][Full Text] [Related]
11. Hierarchical Bayesian sparse image reconstruction with application to MRFM. Dobigeon N; Hero AO; Tourneret JY IEEE Trans Image Process; 2009 Sep; 18(9):2059-70. PubMed ID: 19493849 [TBL] [Abstract][Full Text] [Related]
13. Robust Student's-t mixture model with spatial constraints and its application in medical image segmentation. Nguyen TM; Wu QM IEEE Trans Med Imaging; 2012 Jan; 31(1):103-16. PubMed ID: 21859612 [TBL] [Abstract][Full Text] [Related]
14. Efficient Similarity Point Set Registration by Transformation Decomposition. Wang C; Chen X; Wang M Sensors (Basel); 2020 Jul; 20(15):. PubMed ID: 32717938 [TBL] [Abstract][Full Text] [Related]
16. Maximum likelihood parameter estimation of textures using a Wold-decomposition based model. Francos JM; Narasimhan A; Woods JW IEEE Trans Image Process; 1995; 4(12):1655-66. PubMed ID: 18291996 [TBL] [Abstract][Full Text] [Related]
17. Practical signal-dependent noise parameter estimation from a single noisy image. Liu X; Tanaka M; Okutomi M IEEE Trans Image Process; 2014 Oct; 23(10):4361-71. PubMed ID: 25134082 [TBL] [Abstract][Full Text] [Related]
18. Nonrigid structure-from-motion: estimating shape and motion with hierarchical Priors. Torresani L; Hertzmann A; Bregler C IEEE Trans Pattern Anal Mach Intell; 2008 May; 30(5):878-92. PubMed ID: 18369256 [TBL] [Abstract][Full Text] [Related]
19. Asymmetric mixture model with simultaneous feature selection and model detection. Nguyen TM; Wu QM; Zhang H IEEE Trans Neural Netw Learn Syst; 2015 Feb; 26(2):400-8. PubMed ID: 25608297 [TBL] [Abstract][Full Text] [Related]
20. Bayesian estimation of linear mixtures using the normal compositional model. Application to hyperspectral imagery. Eches O; Dobigeon N; Mailhes C; Tourneret JY IEEE Trans Image Process; 2010 Jun; 19(6):1403-13. PubMed ID: 20215083 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]