Artigos de revistas sobre o tema "MRF, Markov Random Fields"
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Zhipeng, Jiang, e Huang Chengwei. "High-Order Markov Random Fields and Their Applications in Cross-Language Speech Recognition". Cybernetics and Information Technologies 15, n.º 4 (1 de novembro de 2015): 50–57. http://dx.doi.org/10.1515/cait-2015-0054.
Texto completo da fonteCai, Kuntai, Xiaoyu Lei, Jianxin Wei e Xiaokui Xiao. "Data synthesis via differentially private markov random fields". Proceedings of the VLDB Endowment 14, n.º 11 (julho de 2021): 2190–202. http://dx.doi.org/10.14778/3476249.3476272.
Texto completo da fonteLee, Sang Heon, Adel Malallah, Akhil Datta-Gupta e David Higdon. "Multiscale Data Integration Using Markov Random Fields". SPE Reservoir Evaluation & Engineering 5, n.º 01 (1 de fevereiro de 2002): 68–78. http://dx.doi.org/10.2118/76905-pa.
Texto completo da fonteYang, Xiangyu, Xuezhi Yang, Chunju Zhang e Jun Wang. "SAR Image Classification Using Markov Random Fields with Deep Learning". Remote Sensing 15, n.º 3 (20 de janeiro de 2023): 617. http://dx.doi.org/10.3390/rs15030617.
Texto completo da fonteJin, Di, Ziyang Liu, Weihao Li, Dongxiao He e Weixiong Zhang. "Graph Convolutional Networks Meet Markov Random Fields: Semi-Supervised Community Detection in Attribute Networks". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julho de 2019): 152–59. http://dx.doi.org/10.1609/aaai.v33i01.3301152.
Texto completo da fonteSmii, Boubaker. "Markov random fields model and applications to image processing". AIMS Mathematics 7, n.º 3 (2022): 4459–71. http://dx.doi.org/10.3934/math.2022248.
Texto completo da fonteKurella, Pushpak. "Convolutional Neural Networks Grid Search Optimizer Based Brain Tumor Detection". International Transactions on Electrical Engineering and Computer Science 2, n.º 4 (30 de dezembro de 2023): 183–90. http://dx.doi.org/10.62760/iteecs.2.4.2023.68.
Texto completo da fonteShi, Haoran, Lixin Ji, Shuxin Liu, Kai Wang e Xinxin Hu. "Collusive anomalies detection based on collaborative markov random field". Intelligent Data Analysis 26, n.º 6 (12 de novembro de 2022): 1469–85. http://dx.doi.org/10.3233/ida-216287.
Texto completo da fonteKinge, Sanjaykumar, B. Sheela Rani e Mukul Sutaone. "Restored texture segmentation using Markov random fields". Mathematical Biosciences and Engineering 20, n.º 6 (2023): 10063–89. http://dx.doi.org/10.3934/mbe.2023442.
Texto completo da fonteQi, Anna, Lihua Yang e Chao Huang. "Convergence of Markovian stochastic approximation for Markov random fields with hidden variables". Stochastics and Dynamics 20, n.º 05 (18 de novembro de 2019): 2050029. http://dx.doi.org/10.1142/s021949372050029x.
Texto completo da fonteLiu, Lu, e Yongxiang Li. "PolSAR Image Classification with Active Complex-Valued Convolutional-Wavelet Neural Network and Markov Random Fields". Remote Sensing 16, n.º 6 (20 de março de 2024): 1094. http://dx.doi.org/10.3390/rs16061094.
Texto completo da fonteSaon, George, e Abdel Belaïd. "High Performance Unconstrained Word Recognition System Combining HMMs and Markov Random Fields". International Journal of Pattern Recognition and Artificial Intelligence 11, n.º 05 (agosto de 1997): 771–88. http://dx.doi.org/10.1142/s0218001497000342.
Texto completo da fonteYao, Hongtai, Xianpei Wang, Le Zhao, Meng Tian, Zini Jian, Li Gong e Bowen Li. "An Object-Based Markov Random Field with Partition-Global Alternately Updated for Semantic Segmentation of High Spatial Resolution Remote Sensing Image". Remote Sensing 14, n.º 1 (29 de dezembro de 2021): 127. http://dx.doi.org/10.3390/rs14010127.
Texto completo da fonteShu, Zhen, Kai Sun, Kaijin Qiu e Kou Ding. "PAIRWISE-SVM FOR ON-BOARD URBAN ROAD LIDAR CLASSIFICATION". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (2 de junho de 2016): 109–13. http://dx.doi.org/10.5194/isprsarchives-xli-b1-109-2016.
Texto completo da fonteShu, Zhen, Kai Sun, Kaijin Qiu e Kou Ding. "PAIRWISE-SVM FOR ON-BOARD URBAN ROAD LIDAR CLASSIFICATION". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (2 de junho de 2016): 109–13. http://dx.doi.org/10.5194/isprs-archives-xli-b1-109-2016.
Texto completo da fontePlatias, C., M. Vakalopoulou e K. Karantzalos. "AUTOMATIC MRF-BASED REGISTRATION OF HIGH RESOLUTION SATELLITE VIDEO DATA". ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (2 de junho de 2016): 121–28. http://dx.doi.org/10.5194/isprsannals-iii-1-121-2016.
Texto completo da fontePlatias, C., M. Vakalopoulou e K. Karantzalos. "AUTOMATIC MRF-BASED REGISTRATION OF HIGH RESOLUTION SATELLITE VIDEO DATA". ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (2 de junho de 2016): 121–28. http://dx.doi.org/10.5194/isprs-annals-iii-1-121-2016.
Texto completo da fontePratomo, Jati, e Triyoga Widiastomo. "IMPLEMENTATION OF THE MARKOV RANDOM FIELD FOR URBAN LAND COVER CLASSIFICATION OF UAV VHIR DATA". Geoplanning: Journal of Geomatics and Planning 3, n.º 2 (25 de outubro de 2016): 127. http://dx.doi.org/10.14710/geoplanning.3.2.127-136.
Texto completo da fonteYin, Junjun, Xiyun Liu, Jian Yang, Chih-Yuan Chu e Yang-Lang Chang. "PolSAR Image Classification Based on Statistical Distribution and MRF". Remote Sensing 12, n.º 6 (23 de março de 2020): 1027. http://dx.doi.org/10.3390/rs12061027.
Texto completo da fonteLee, Sangkyun, Piotr Sobczyk e Malgorzata Bogdan. "Structure Learning of Gaussian Markov Random Fields with False Discovery Rate Control". Symmetry 11, n.º 10 (18 de outubro de 2019): 1311. http://dx.doi.org/10.3390/sym11101311.
Texto completo da fonteLenin Kumar Reddy, Sama, C. V. Rao e P. Rajesh Kumar. "Road Feature Extraction from LANDSAT-8 and ResourceSat-2 Images". Russian Journal of Earth Sciences 21, n.º 3 (2021): 1–9. http://dx.doi.org/10.2205/2021es000772.
Texto completo da fonteAndrejchenko, Vera, Wenzhi Liao, Wilfried Philips e Paul Scheunders. "Decision Fusion Framework for Hyperspectral Image Classification Based on Markov and Conditional Random Fields". Remote Sensing 11, n.º 6 (14 de março de 2019): 624. http://dx.doi.org/10.3390/rs11060624.
Texto completo da fonteWu, Yongji, Defu Lian, Yiheng Xu, Le Wu e Enhong Chen. "Graph Convolutional Networks with Markov Random Field Reasoning for Social Spammer Detection". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 01 (3 de abril de 2020): 1054–61. http://dx.doi.org/10.1609/aaai.v34i01.5455.
Texto completo da fonteKumar Reddy, Sama Lenin, C. V. Rao, P. Rajesh Kumar, R. V. G. Anjaneyulu e B. Gopala Krishna. "An index based road feature extraction from LANDSAT-8 OLI images". International Journal of Electrical and Computer Engineering (IJECE) 11, n.º 2 (1 de abril de 2021): 1319. http://dx.doi.org/10.11591/ijece.v11i2.pp1319-1336.
Texto completo da fonteWerbos, Paul J. "Stochastic Path Model of Polaroid Polarizer for Bell's Theorem and Triphoton Experiments". International Journal of Bifurcation and Chaos 25, n.º 03 (março de 2015): 1550046. http://dx.doi.org/10.1142/s0218127415500467.
Texto completo da fonteHe, Xu, e Yong Yin. "Non-Local and Multi-Scale Mechanisms for Image Inpainting". Sensors 21, n.º 9 (10 de maio de 2021): 3281. http://dx.doi.org/10.3390/s21093281.
Texto completo da fonteBrimkulov, Ulan. "Matrices whose inverses are tridiagonal, band or block-tridiagonal and their relationship with the covariance matrices of a random Markov process". Filomat 33, n.º 5 (2019): 1335–52. http://dx.doi.org/10.2298/fil1905335b.
Texto completo da fonteWang, Jie, Bensheng Huang e Fuming Wang. "Extraction and Classification of Flood-Affected Areas Based on MRF and Deep Learning". Water 15, n.º 7 (24 de março de 2023): 1288. http://dx.doi.org/10.3390/w15071288.
Texto completo da fonteNex, F., E. Rupnik, I. Toschi e F. Remondino. "Automated processing of high resolution airborne images for earthquake damage assessment". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1 (7 de novembro de 2014): 315–21. http://dx.doi.org/10.5194/isprsarchives-xl-1-315-2014.
Texto completo da fonteDong, Tianzhen, Yi Zhang, Mengying Li e Yuntao Bai. "Point Cloud Repair Method via Convex Set Theory". Applied Sciences 13, n.º 3 (31 de janeiro de 2023): 1830. http://dx.doi.org/10.3390/app13031830.
Texto completo da fonteCooper, M. C., e S. Zivny. "Tractable Triangles and Cross-Free Convexity in Discrete Optimisation". Journal of Artificial Intelligence Research 44 (27 de julho de 2012): 455–90. http://dx.doi.org/10.1613/jair.3598.
Texto completo da fonteMELGANI, FARID. "CLASSIFICATION OF MULTITEMPORAL REMOTE-SENSING IMAGES BY A FUZZY FUSION OF SPECTRAL AND SPATIO-TEMPORAL CONTEXTUAL INFORMATION". International Journal of Pattern Recognition and Artificial Intelligence 18, n.º 02 (março de 2004): 143–56. http://dx.doi.org/10.1142/s0218001404003083.
Texto completo da fonteAbuhussein, Mohammed, e Aaron Robinson. "Obscurant Segmentation in Long Wave Infrared Images Using GLCM Textures". Journal of Imaging 8, n.º 10 (30 de setembro de 2022): 266. http://dx.doi.org/10.3390/jimaging8100266.
Texto completo da fonteMing, Yansheng, e Zhanyi Hu. "Modeling Stereopsis via Markov Random Field". Neural Computation 22, n.º 8 (agosto de 2010): 2161–91. http://dx.doi.org/10.1162/neco_a_00005-ming.
Texto completo da fonteChen, S. Y., Hanyang Tong e Carlo Cattani. "Markov Models for Image Labeling". Mathematical Problems in Engineering 2012 (2012): 1–18. http://dx.doi.org/10.1155/2012/814356.
Texto completo da fonteMat Said, K. A., e A. B. Jambek. "DNA Microarray Image Segmentation Using Markov Random Field Algorithm". Journal of Physics: Conference Series 2071, n.º 1 (1 de outubro de 2021): 012032. http://dx.doi.org/10.1088/1742-6596/2071/1/012032.
Texto completo da fonteZhao, J., G. Huang e Z. Zhao. "SAR IMAGE CHANGE DETECTION BASED ON FUZZY MARKOV RANDOM FIELD MODEL". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (30 de abril de 2018): 2371–74. http://dx.doi.org/10.5194/isprs-archives-xlii-3-2371-2018.
Texto completo da fonteCui, Yan Qiu, Tao Zhang, Shuang Xu e Hou Jie Li. "Bayesian Image Denoising Using an Anisotropic Markov Random Field Model". Key Engineering Materials 467-469 (fevereiro de 2011): 2018–23. http://dx.doi.org/10.4028/www.scientific.net/kem.467-469.2018.
Texto completo da fonteSalih, Omran, e Serestina Viriri. "Skin Lesion Segmentation Using Stochastic Region-Merging and Pixel-Based Markov Random Field". Symmetry 12, n.º 8 (26 de julho de 2020): 1224. http://dx.doi.org/10.3390/sym12081224.
Texto completo da fonteChávez, Ricardo Omar, Hugo Jair Escalante, Manuel Montes-y-Gómez e Luis Enrique Sucar. "Multimodal Markov Random Field for Image Reranking Based on Relevance Feedback". ISRN Machine Vision 2013 (11 de fevereiro de 2013): 1–16. http://dx.doi.org/10.1155/2013/428746.
Texto completo da fonteChyan, Phie, e N. Tri Saptadi. "Pemulihan Citra Berbasis Metode Markov Random Field". JURIKOM (Jurnal Riset Komputer) 9, n.º 2 (29 de abril de 2022): 218. http://dx.doi.org/10.30865/jurikom.v9i2.3966.
Texto completo da fonteRota, Gian-Carlo. "Markov random fields". Advances in Mathematics 57, n.º 2 (agosto de 1985): 208. http://dx.doi.org/10.1016/0001-8708(85)90060-x.
Texto completo da fonteJung, Myung Hee, Eui Jung Yun e Sy Woo Byun. "Utilization of Markov Random Field for Large Images: Multiframe Work and Bayesian Approach". Key Engineering Materials 277-279 (janeiro de 2005): 183–88. http://dx.doi.org/10.4028/www.scientific.net/kem.277-279.183.
Texto completo da fontePanić, Marko, Dušan Jakovetić, Dejan Vukobratović, Vladimir Crnojević e Aleksandra Pižurica. "MRI Reconstruction Using Markov Random Field and Total Variation as Composite Prior". Sensors 20, n.º 11 (3 de junho de 2020): 3185. http://dx.doi.org/10.3390/s20113185.
Texto completo da fonteJing, Junfeng, Qi Li, Pengfei Li, Hongwei Zhang e Lei Zhang. "Image Segmentation of Printed Fabrics with Hierarchical Improved Markov Random Field in the Wavelet Domain". Journal of Engineered Fibers and Fabrics 11, n.º 3 (setembro de 2016): 155892501601100. http://dx.doi.org/10.1177/155892501601100305.
Texto completo da fonteKunsch, Hans, Stuart Geman e Athanasios Kehagias. "Hidden Markov Random Fields". Annals of Applied Probability 5, n.º 3 (agosto de 1995): 577–602. http://dx.doi.org/10.1214/aoap/1177004696.
Texto completo da fonteCarstensen, Jens Michael. "Morphological Markov random fields". Statistics & Probability Letters 20, n.º 4 (julho de 1994): 321–26. http://dx.doi.org/10.1016/0167-7152(94)90020-5.
Texto completo da fonteChandgotia, Nishant, Guangyue Han, Brian Marcus, Tom Meyerovitch e Ronnie Pavlov. "One-dimensional Markov random fields, Markov chains and topological Markov fields". Proceedings of the American Mathematical Society 142, n.º 1 (3 de outubro de 2013): 227–42. http://dx.doi.org/10.1090/s0002-9939-2013-11741-7.
Texto completo da fonteLahouaoui, Lalaoui, e Djaalab Abdelhak. "Markov random field model and expectation of maximization for images segmentation". Indonesian Journal of Electrical Engineering and Computer Science 29, n.º 2 (1 de fevereiro de 2023): 772. http://dx.doi.org/10.11591/ijeecs.v29.i2.pp772-779.
Texto completo da fontePanda, Sucheta, e P. K. Nanda. "Constrained Compound Markov Random Field Model with Graduated Penalty Function for Color Image Segmentation". Advanced Materials Research 403-408 (novembro de 2011): 3438–45. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.3438.
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