Articoli di riviste sul tema "Segmentation multivariée"
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Klose, J. "Binary Segmentation for Multivariate Polynomials". Journal of Complexity 11, n. 3 (settembre 1995): 330–43. http://dx.doi.org/10.1006/jcom.1995.1015.
Neubauer, Jakob, Konrad Wilhelm, Christian Gratzke, Fabian Bamberg, Marco Reisert e Elias Kellner. "Effect of surface-partial-volume correction and adaptive threshold on segmentation of uroliths in computed tomography". PLOS ONE 18, n. 6 (23 giugno 2023): e0286016. http://dx.doi.org/10.1371/journal.pone.0286016.
Esteban, Oscar, Gert Wollny, Subrahmanyam Gorthi, María-J. Ledesma-Carbayo, Jean-Philippe Thiran, Andrés Santos e Meritxell Bach-Cuadra. "MBIS: Multivariate Bayesian Image Segmentation tool". Computer Methods and Programs in Biomedicine 115, n. 2 (luglio 2014): 76–94. http://dx.doi.org/10.1016/j.cmpb.2014.03.003.
Portillo-García, J., I. Trueba-Santander, G. de Miguel-Vela e C. Alberola-López. "Efficient multispectral texture segmentation using multivariate statistics". IEE Proceedings - Vision, Image, and Signal Processing 145, n. 5 (1998): 357. http://dx.doi.org/10.1049/ip-vis:19982315.
Lim, Hyunki, Heeseung Choi, Yeji Choi e Ig-Jae Kim. "Memetic algorithm for multivariate time-series segmentation". Pattern Recognition Letters 138 (ottobre 2020): 60–67. http://dx.doi.org/10.1016/j.patrec.2020.06.022.
Hallac, David, Peter Nystrup e Stephen Boyd. "Greedy Gaussian segmentation of multivariate time series". Advances in Data Analysis and Classification 13, n. 3 (22 agosto 2018): 727–51. http://dx.doi.org/10.1007/s11634-018-0335-0.
Sudbury, Lynn, e Peter Simcock. "A multivariate segmentation model of senior consumers". Journal of Consumer Marketing 26, n. 4 (26 giugno 2009): 251–62. http://dx.doi.org/10.1108/07363760910965855.
Laksono, Bagaskoro Cahyo, e Ika Yuni Wulansari. "Estimating Customer Lifetime Value in the E-Commerce Industry Using Multivariate Analysis". Proceedings of The International Conference on Data Science and Official Statistics 2021, n. 1 (4 gennaio 2022): 507–18. http://dx.doi.org/10.34123/icdsos.v2021i1.161.
Omranian, Nooshin, Sebastian Klie, Bernd Mueller-Roeber e Zoran Nikoloski. "Network-Based Segmentation of Biological Multivariate Time Series". PLoS ONE 8, n. 5 (7 maggio 2013): e62974. http://dx.doi.org/10.1371/journal.pone.0062974.
Ip, Barry, e Gabriel Jacobs. "Segmentation of the games market using multivariate analysis". Journal of Targeting, Measurement and Analysis for Marketing 13, n. 3 (aprile 2005): 275–87. http://dx.doi.org/10.1057/palgrave.jt.5740154.
Noordam, J. C., W. H. A. M. van den Broek e L. M. C. Buydens. "Unsupervised segmentation of predefined shapes in multivariate images". Journal of Chemometrics 17, n. 4 (2003): 216–24. http://dx.doi.org/10.1002/cem.794.
Guo, Hongyue, Xiaodong Liu e Lixin Song. "Dynamic programming approach for segmentation of multivariate time series". Stochastic Environmental Research and Risk Assessment 29, n. 1 (21 maggio 2014): 265–73. http://dx.doi.org/10.1007/s00477-014-0897-0.
Wang, Ling, Kang Li, Qian Ma e YanRong Lu. "Hybrid dynamic learning mechanism for multivariate time series segmentation". Statistical Analysis and Data Mining: The ASA Data Science Journal 13, n. 2 (25 gennaio 2020): 165–77. http://dx.doi.org/10.1002/sam.11448.
K. Naveen Kumar,. "Multivariate Approach for Texture Segmentation using Probabilistic Statistical Model". Journal of Electrical Systems 20, n. 2 (4 aprile 2024): 2381–85. http://dx.doi.org/10.52783/jes.2003.
Cao, Haoyin, Andrea Morotti, Federico Mazzacane, Dmitriy Desser, Frieder Schlunk, Christopher Güttler, Helge Kniep et al. "External Validation and Retraining of DeepBleed: The First Open-Source 3D Deep Learning Network for the Segmentation of Spontaneous Intracerebral and Intraventricular Hemorrhage". Journal of Clinical Medicine 12, n. 12 (12 giugno 2023): 4005. http://dx.doi.org/10.3390/jcm12124005.
Lei, Tao, Yi Wang e Weiwei Luo. "Multivariate Self-Dual Morphological Operators Based on Extremum Constraint". Mathematical Problems in Engineering 2015 (2015): 1–16. http://dx.doi.org/10.1155/2015/596348.
Castro-López, Claudio, Purificación Vicente-Galindo, Purificación Galindo-Villardón e Oscar Borrego-Hernández. "TAID-LCA: Segmentation Algorithm Based on Ternary Trees". Mathematics 10, n. 4 (11 febbraio 2022): 560. http://dx.doi.org/10.3390/math10040560.
Noyel, Guillaume, Jesus Angulo, Dominique Jeulin, Daniel Balvay e Charles-André Cuenod. "MULTIVARIATE MATHEMATICAL MORPHOLOGY FOR DCE-MRI IMAGE ANALYSIS IN ANGIOGENESIS STUDIES". Image Analysis & Stereology 34, n. 1 (30 maggio 2014): 1. http://dx.doi.org/10.5566/ias.1109.
ANJUM, ARFA, SEEMA JAGGI, SHWETANK LALL, ELDHO VARGHESE, ANIL RAI, ARPAN BHOWMIK e DWIJESH CHANDRA MISHRA. "Segmentation of genomic data through multivariate statistical approaches: comparative analysis". Indian Journal of Agricultural Sciences 92, n. 7 (30 marzo 2022): 892–96. http://dx.doi.org/10.56093/ijas.v92i7.118040.
Li, Min, e Yu-Mei Huang. "An $L_0$-Norm Regularized Method for Multivariate Time Series Segmentation". East Asian Journal on Applied Mathematics 12, n. 2 (giugno 2022): 353–66. http://dx.doi.org/10.4208/eajam.180921.050122.
Somasekhar, G., K. Srinivasa Krishna, Ashok Kumar Reddy, T. Kishore Kumar e G. Somasekhar. "Shopper Segmentation Using Multivariate Risk Analysis for Innovative Marketing Strategies". International Journal of Asian Business and Information Management 12, n. 1 (gennaio 2021): 60–74. http://dx.doi.org/10.4018/ijabim.20210101.oa4.
Hosseini, Jamshid C., Robert R. Harmon e Martin Zwick. "An Information Theoretic Framework for Exploratory Multivariate Market Segmentation Research". Decision Sciences 22, n. 3 (luglio 1991): 663–77. http://dx.doi.org/10.1111/j.1540-5915.1991.tb01289.x.
Piccolboni, Antonio. "Multivariate Segmentation in the Analysis of Transcription Tiling Array Data". Journal of Computational Biology 15, n. 7 (settembre 2008): 845–56. http://dx.doi.org/10.1089/cmb.2007.0141.
Zhuang, Xiahai. "Multivariate Mixture Model for Myocardial Segmentation Combining Multi-Source Images". IEEE Transactions on Pattern Analysis and Machine Intelligence 41, n. 12 (1 dicembre 2019): 2933–46. http://dx.doi.org/10.1109/tpami.2018.2869576.
Willse, Alan, e Bonnie Tyler. "Poisson and Multinomial Mixture Models for Multivariate SIMS Image Segmentation". Analytical Chemistry 74, n. 24 (dicembre 2002): 6314–22. http://dx.doi.org/10.1021/ac025561i.
Noordam, J. C., W. H. A. M. van den Broek e L. M. C. Buydens. "Multivariate image segmentation with cluster size insensitive Fuzzy C-means". Chemometrics and Intelligent Laboratory Systems 64, n. 1 (ottobre 2002): 65–78. http://dx.doi.org/10.1016/s0169-7439(02)00052-7.
Lambert, Christian, Antoine Lutti, Gunther Helms, Richard Frackowiak e John Ashburner. "Multiparametric brainstem segmentation using a modified multivariate mixture of Gaussians". NeuroImage: Clinical 2 (2013): 684–94. http://dx.doi.org/10.1016/j.nicl.2013.04.017.
Hazel, G. G. "Multivariate Gaussian MRF for multispectral scene segmentation and anomaly detection". IEEE Transactions on Geoscience and Remote Sensing 38, n. 3 (maggio 2000): 1199–211. http://dx.doi.org/10.1109/36.843012.
Li, Min, Yumei Huang null e Youwei Wen. "A Total Variation Based Method for Multivariate Time Series Segmentation". Advances in Applied Mathematics and Mechanics 15, n. 2 (giugno 2023): 300–321. http://dx.doi.org/10.4208/aamm.oa-2021-0209.
Picard, F., E. Lebarbier, E. Budinskà e S. Robin. "Joint segmentation of multivariate Gaussian processes using mixed linear models". Computational Statistics & Data Analysis 55, n. 2 (febbraio 2011): 1160–70. http://dx.doi.org/10.1016/j.csda.2010.09.015.
Lu, Chang, Jiyou Fei, Xing Zhao e Xiongfei Shao. "Laser Cutting Thermal Error Prediction Method Based on Multivariate Segmentation". Journal of Physics: Conference Series 2541, n. 1 (1 luglio 2023): 012027. http://dx.doi.org/10.1088/1742-6596/2541/1/012027.
UR, Orth, e J. Turečková. "Segmenting the tourism market using perceptual and attitudinal mapping". Agricultural Economics (Zemědělská ekonomika) 48, No. 1 (29 febbraio 2012): 36–48. http://dx.doi.org/10.17221/5286-agricecon.
Mishulina, O. A., e I. N. Sukonkin. "Multivariate time series segmentation for generalized description of dynamic systems operation". Optical Memory and Neural Networks 21, n. 2 (aprile 2012): 94–104. http://dx.doi.org/10.3103/s1060992x12020038.
Ma, Yi, Harm Derksen, Wei Hong e John Wright. "Segmentation of Multivariate Mixed Data via Lossy Data Coding and Compression". IEEE Transactions on Pattern Analysis and Machine Intelligence 29, n. 9 (settembre 2007): 1546–62. http://dx.doi.org/10.1109/tpami.2007.1085.
Schenone, A., F. Firenze, F. Acquarone, M. Gambaro, F. Masulli e L. Andreucci. "Segmentation of multivariate medical images via unsupervised clustering with “adaptive resolution”". Computerized Medical Imaging and Graphics 20, n. 3 (maggio 1996): 119–29. http://dx.doi.org/10.1016/0895-6111(96)00008-0.
Liu, Zhe, Yu-Qing Song, Jian-Mei Chen, Cong-Hua Xie e Feng Zhu. "Color image segmentation using nonparametric mixture models with multivariate orthogonal polynomials". Neural Computing and Applications 21, n. 4 (16 febbraio 2011): 801–11. http://dx.doi.org/10.1007/s00521-011-0538-1.
Abonyi, Janos, Balazs Feil, Sandor Nemeth e Peter Arva. "Modified Gath–Geva clustering for fuzzy segmentation of multivariate time-series". Fuzzy Sets and Systems 149, n. 1 (gennaio 2005): 39–56. http://dx.doi.org/10.1016/j.fss.2004.07.008.
Wang, Ling, Hui Zhu e Gaofeng Jia. "Adaptive G–G clustering for fuzzy segmentation of multivariate time series". Stochastic Environmental Research and Risk Assessment 34, n. 9 (2 giugno 2020): 1353–67. http://dx.doi.org/10.1007/s00477-020-01817-w.
Tanatavikorn, Harakhun, e Yoshiyuki Yamashita. "Batch Process Monitoring Based on Fuzzy Segmentation of Multivariate Time-Series". Journal of Chemical Engineering of Japan 50, n. 1 (2017): 53–63. http://dx.doi.org/10.1252/jcej.16we193.
Han, Minyeon, e F. C. Park. "DTI Segmentation and Fiber Tracking Using Metrics on Multivariate Normal Distributions". Journal of Mathematical Imaging and Vision 49, n. 2 (6 dicembre 2013): 317–34. http://dx.doi.org/10.1007/s10851-013-0466-z.
Qin, A. K., e David A. Clausi. "Multivariate Image Segmentation Using Semantic Region Growing With Adaptive Edge Penalty". IEEE Transactions on Image Processing 19, n. 8 (agosto 2010): 2157–70. http://dx.doi.org/10.1109/tip.2010.2045708.
Lazar, Cosmin, Andrei Doncescu e Nabil Kabbaj. "Non Negative Matrix Factorisation clustering capabilities; application on multivariate image segmentation". International Journal of Business Intelligence and Data Mining 5, n. 3 (2010): 285. http://dx.doi.org/10.1504/ijbidm.2010.033363.
Ding, Mingtao, Lihan He, David Dunson e Lawrence Carin. "Nonparametric Bayesian Segmentation of a Multivariate Inhomogeneous Space-Time Poisson Process". Bayesian Analysis 7, n. 4 (dicembre 2012): 813–40. http://dx.doi.org/10.1214/12-ba727.
Noordam, J. C., e W. H. A. M. van den Broek. "Multivariate image segmentation based on geometrically guided fuzzy C-means clustering". Journal of Chemometrics 16, n. 1 (gennaio 2002): 1–11. http://dx.doi.org/10.1002/cem.656.
Wang, Ling, e Peng Shen. "Memetic segmentation based on variable lag aware for multivariate time series". Information Sciences 657 (febbraio 2024): 120003. http://dx.doi.org/10.1016/j.ins.2023.120003.
Zhang, Changrui, e Jia Wang. "PIS-Net: Efficient Medical Image Segmentation Network with Multivariate Downsampling for Point-of-Care". Entropy 26, n. 4 (26 marzo 2024): 284. http://dx.doi.org/10.3390/e26040284.
Dai, Bing, Yingjie Peng, Ning Lin e Peng Wang. "Bearing Fault Diagnosis Based on Prime Mean Spectral Segmentation Kurtogram". Journal of Physics: Conference Series 2419, n. 1 (1 gennaio 2023): 012080. http://dx.doi.org/10.1088/1742-6596/2419/1/012080.
Gaugel, Stefan, e Manfred Reichert. "Industrial Transfer Learning for Multivariate Time Series Segmentation: A Case Study on Hydraulic Pump Testing Cycles". Sensors 23, n. 7 (31 marzo 2023): 3636. http://dx.doi.org/10.3390/s23073636.
Banas, Krzysztof, Agnieszka Banas, Mariusz Gajda, Bohdan Pawlicki, Wojciech M. Kwiatek e Mark B. H. Breese. "Pre-processing of Fourier transform infrared spectra by means of multivariate analysis implemented in the R environment". Analyst 140, n. 8 (2015): 2810–14. http://dx.doi.org/10.1039/c5an00002e.
Lim, Jong Gwan, Mi-hye Kim e Sahngwoon Lee. "Empirical Validation of Objective Functions in Feature Selection Based on Acceleration Motion Segmentation Data". Mathematical Problems in Engineering 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/280140.