Literatura científica selecionada sobre o tema "Analyse supervisée"
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Artigos de revistas sobre o assunto "Analyse supervisée"
Berriche, Amira, Dominique Crié e Michel Calciu. "Une Approche Computationnelle Ancrée : Étude de cas des tweets du challenge #Movember en prévention de santé masculine". Décisions Marketing N° 112, n.º 4 (25 de janeiro de 2024): 79–103. http://dx.doi.org/10.3917/dm.112.0079.
Texto completo da fonteGlendenning, Jonathan. "Espace disciplinaire et normativité sociale contemporaine". Perspectives étatiques 28, n.º 1 (15 de março de 2017): 195–210. http://dx.doi.org/10.7202/1039181ar.
Texto completo da fonteIdrissa, Ali, Amani Abdou, Barmo Soukaradji, Ibrahim Biga e Ali Mahamane. "Analyse spatiotemporelle de l’occupation du sol dans la commune de Kirtachi au sud-ouest du Niger". International Journal of Biological and Chemical Sciences 17, n.º 3 (24 de agosto de 2023): 1033–47. http://dx.doi.org/10.4314/ijbcs.v17i3.22.
Texto completo da fonteJuge, P. A., B. Granger, L. El Houari, G. Mcdermott, T. Doyle, C. Kelly, K. Gouri et al. "Déchiffrer la pneumopathie interstitielle diffuse associée à la polyarthrite rhumatoïde en utilisant une analyse en cluster hiérarchique non supervisée : résultats d’une collaboration internationale". Revue du Rhumatisme 90 (dezembro de 2023): A27—A28. http://dx.doi.org/10.1016/j.rhum.2023.10.040.
Texto completo da fonteTegno Nguekam, Eric Wilson, Salomon C. Nguemhe Fils, Joachim Etouna e Simon Njeudeng Tenku. "ANALYSE DE LA DEFORESTATION DANS LA PERIPHERIE OUEST DE LA RESERVE DE BIOSPHERE DU DJA AU CAMEROUN, A PARTIR D'UNE SERIE MULTI-ANNUELLE D'IMAGES LANDSAT". Revue Française de Photogrammétrie et de Télédétection, n.º 222 (26 de novembro de 2020): 31–41. http://dx.doi.org/10.52638/rfpt.2020.434.
Texto completo da fonteGanachaud, Clément, Ludovic Seifert e David Adé. "L’importation de méthodes non-supervisées en fouille de données dans le programme de recherche empirique et technologique du cours d’action : Apports et réflexions critiques". Staps N° 141, n.º 3 (17 de janeiro de 2024): 97–108. http://dx.doi.org/10.3917/sta.141.0097.
Texto completo da fonteTesta, D., N. Jourde-Chiche, J. Mancini, P. Varriale, V. Morisseau, L. Radoszycki e L. Chiche. "Analyse en clusters non supervisée des données en vie réelle d’une communauté en ligne de patients lupiques pour identifier des profils concernant leurs préférences thérapeutiques". La Revue de Médecine Interne 42 (junho de 2021): A85. http://dx.doi.org/10.1016/j.revmed.2021.03.306.
Texto completo da fonteTörnquist, Anna, Sarah Rakovshik, Jan Carlsson e Joakim Norberg. "How Supervisees on a Foundation Course in CBT Perceive a Supervision Session and what they Bring Forward to the Next Therapy Session". Behavioural and Cognitive Psychotherapy 46, n.º 3 (14 de setembro de 2017): 302–17. http://dx.doi.org/10.1017/s1352465817000558.
Texto completo da fonteBencherif, Kada, e Houari Tadj. "Approche d'estimation du volume-tige de peuplements forestiers par combinaison de données Landsat et données terrain Application à la pineraie de Tlemcen-Algérie". Revue Française de Photogrammétrie et de Télédétection, n.º 215 (16 de agosto de 2017): 3–11. http://dx.doi.org/10.52638/rfpt.2017.360.
Texto completo da fonteWils, Thierry, e Aziz Rhnima. "Taxonomie des conflits entre le travail et la famille : une analyse multidimensionnelle à l’aide de cartes auto-organisatrices". Articles 70, n.º 3 (5 de outubro de 2015): 432–56. http://dx.doi.org/10.7202/1033405ar.
Texto completo da fonteTeses / dissertações sobre o assunto "Analyse supervisée"
Debeir, Olivier. "Segmentation supervisée d'images". Doctoral thesis, Universite Libre de Bruxelles, 2001. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/211474.
Texto completo da fonteGoubet, Étienne. "Contrôle non destructif par analyse supervisée d'images 3D ultrasonores". Cachan, Ecole normale supérieure, 1999. http://www.theses.fr/1999DENS0011.
Texto completo da fonteHuck, Alexis. "Analyse non-supervisée d’images hyperspectrales : démixage linéaire et détection d’anomalies". Aix-Marseille 3, 2009. http://www.theses.fr/2009AIX30036.
Texto completo da fonteThis thesis focusses on two research fields regarding unsupervised analysis of hyperspectral images (HSIs). Under the assumptions of the linear spectral mixing model, the formalism of Non-Negative Matrix Factorization is investigated for unmixing purposes. We propose judicious spectral and spatial a priori knowledge to regularize the problem. In addition, we propose an estimator for the projected gradient optimal step-size. Thus, suitably regularized NMF is shown to be a relevant approach to unmix HSIs. Then, the problem of anomaly detection is considered. We propose an algorithm for Anomalous Component Pursuit (ACP), simultaneously based on projection pursuit and on a probabilistic model and hypothesis testing. ACP detects the anomalies with a constant false alarm rate and discriminates them into spectrally homogeneous classes
Chombart, Anne. "Commande supervisée de systèmes hybrides". Grenoble INPG, 1997. http://www.theses.fr/1997INPG0170.
Texto completo da fonteFaucheux, Cyrille. "Segmentation supervisée d'images texturées par régularisation de graphes". Thesis, Tours, 2013. http://www.theses.fr/2013TOUR4050/document.
Texto completo da fonteIn this thesis, we improve a recent image segmentation algorithm based on a graph regularization process. The goal of this method is to compute an indicator function that satisfies a regularity and a fidelity criteria. Its particularity is to represent images with similarity graphs. This data structure allows relations to be established between similar pixels, leading to non-local processing of the data. In order to improve this approach, combine it with another non-local one: the texture features. Two solutions are developped, both based on Haralick features. In the first one, we propose a new fidelity term which is based on the work of Chan and Vese and is able to evaluate the homogeneity of texture features. In the second method, we propose to replace the fidelity criteria by the output of a supervised classifier. Trained to recognize several textures, the classifier is able to produce a better modelization of the problem by identifying the most relevant texture features. This method is also extended to multiclass segmentation problems. Both are applied to 2D and 3D textured images
Dârlea, Georgiana-Lavinia. "Un système de classification supervisée à base de règles implicatives". Chambéry, 2010. http://www.theses.fr/2010CHAMS001.
Texto completo da fonteThis PhD thesis presents a series of research works done in the field of supervised data classification more precisely in the domain of semi-automatic learning of fuzzy rules-based classifiers. The prepared manuscript presents first an overview of the classification problem, and also of the main classification methods that have already been implemented and certified in order to place the proposed method in the general context of the domain. Once the context established, the actual research work is presented: the definition of a formal background for representing an elementary fuzzy rule-based classifier in a bi-dimensional space, the description of a learning algorithm for these elementary classifiers for a given data set and the conception of a multi-dimensional classification system which is able to handle multi-classes problems by combining the elementary classifiers. The implementation and testing of all these functionalities and finally the application of the resulted classifier on two real-world digital image problems are finally presented: the analysis of the quality of industrial products using 3D tomographic images and the identification of regions of interest in radar satellite images
Leblanc, Brice. "Analyse non supervisée de données issues de Systèmes de Transport Intelligent-Coopératif". Thesis, Reims, 2020. http://www.theses.fr/2020REIMS014.
Texto completo da fonteThis thesis takes place in the context of Vehicular Ad-hoc Networks (VANET), and more specifically the context of Cooperative-Intelligent Transport System (C-ITS). These systems are exchanging information to enhance road safety.The purpose of this thesis is to introduce data analysis tools that may provide road operators information on the usage/state of their infrastructures. Therefore, this information may help to improve road safety. We identify two cases we want to deal with: driving profile identification and road obstacle detection.For dealing with those issues, we propose to use unsupervised learning approaches: clustering methods for driving profile identification, and concept drift detection for obstacle detection. This thesis introduces three main contributions: a methodology allowing us to transform raw C-ITS data in, first, trajectory, and then, learning data-set; the use of classical clustering methods and Points Of Interests for driving profiles with experiments on mobile device data and network logs data; and the consideration of a crowd of vehicles providing network log data as data streams and considered as input of concept drift detection algorithms to recognize road obstacles
Fontaine, Michaël. "Segmentation non supervisée d'images couleur par analyse de la connexité des pixels". Lille 1, 2001. https://pepite-depot.univ-lille.fr/LIBRE/Th_Num/2001/50376-2001-305-306.pdf.
Texto completo da fonteConan-Guez, Brieuc. "Modélisation supervisée de données fonctionnelles par perceptron multi-couches". Phd thesis, Université Paris Dauphine - Paris IX, 2002. http://tel.archives-ouvertes.fr/tel-00178892.
Texto completo da fonteVandewalle, Vincent. "Estimation et sélection en classification semi-supervisée". Phd thesis, Université des Sciences et Technologie de Lille - Lille I, 2009. http://tel.archives-ouvertes.fr/tel-00447141.
Texto completo da fonteLivros sobre o assunto "Analyse supervisée"
Catoni, Olivier. PAC-Bayesian supervised classification: The thermodynamics of statistical learning. Beachwood, Ohio: Institute of Mathematical Statistics, 2007.
Encontre o texto completo da fonteZutter, Jörg. Projekt eines Antikenmuseums von D.P.G. Humbert de Superville (1770-1849): Entstehungsgeschichte, Rekonstruktion und Analyse, kunsttheoretischer Kontext, Vergleich mit Antikensammlungen, Museen und Denkmälern der Zeit. München: Tuduv, 1991.
Encontre o texto completo da fonteAnikin, Valeriy, e Boris Poyzner. To the dissertation dissertation: the semantic aspect. ru: INFRA-M Academic Publishing LLC., 2024. http://dx.doi.org/10.12737/1909143.
Texto completo da fonteCorporation, National Learning. Workforce Development Analyst/Supervisor: Passbooks Study Guide. National Learning Corporation, 2016.
Encontre o texto completo da fonteSingh, Dalvinder. European Cross-Border Banking and Banking Supervision. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198844754.001.0001.
Texto completo da fontePartially Supervised Learning. Springer-Verlag Berlin and Heidelberg GmbH &, 2012.
Encontre o texto completo da fonteApplications Of Supervised And Unsupervised Ensemble Methods. Springer, 2009.
Encontre o texto completo da fonteBaillo, Amparo, Antonio Cuevas e Ricardo Fraiman. Classification methods for functional data. Editado por Frédéric Ferraty e Yves Romain. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199568444.013.10.
Texto completo da fonteRodrigo, Olivares-Caminal, Douglas John, Guynn Randall, Kornberg Alan, Paterson Sarah e Singh Dalvinder. Part I Corporate Debt Restructuring, 3 Out-of-Court vs Court-Supervised Restructurings. Oxford University Press, 2016. http://dx.doi.org/10.1093/law/9780198725244.003.0003.
Texto completo da fonteVarol, Ozan O. Golden Parachutes. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190626013.003.0017.
Texto completo da fonteCapítulos de livros sobre o assunto "Analyse supervisée"
Cerulli, Giovanni. "Sentiment Analysis". In Fundamentals of Supervised Machine Learning, 365–84. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-41337-7_8.
Texto completo da fonteVerdhan, Vaibhav. "Supervised Learning for Regression Analysis". In Supervised Learning with Python, 47–116. Berkeley, CA: Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-6156-9_2.
Texto completo da fonteAggarwal, Charu C. "Supervised Outlier Detection". In Outlier Analysis, 219–48. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47578-3_7.
Texto completo da fonteAggarwal, Charu C. "Supervised Outlier Detection". In Outlier Analysis, 169–98. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-6396-2_6.
Texto completo da fonteMark, Howard. "Supervised Methods". In Handbook of Near-Infrared Analysis, 211–33. 4a ed. Fourth edition. | Boca Raton : Taylor and Francis, 2021. |: CRC Press, 2021. http://dx.doi.org/10.1201/b22513-15.
Texto completo da fonteRiese, Felix M., e Sina Keller. "Supervised, Semi-supervised, and Unsupervised Learning for Hyperspectral Regression". In Hyperspectral Image Analysis, 187–232. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38617-7_7.
Texto completo da fonteM. Bagirov, Adil, Napsu Karmitsa e Sona Taheri. "Optimization Models in Cluster Analysis". In Unsupervised and Semi-Supervised Learning, 97–133. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-37826-4_4.
Texto completo da fonteMarron, J. S., e Ian L. Dryden. "Classification–Supervised Learning". In Object Oriented Data Analysis, 215–42. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781351189675-11.
Texto completo da fonteRafatirad, Setareh, Houman Homayoun, Zhiqian Chen e Sai Manoj Pudukotai Dinakarrao. "Supervised Learning". In Machine Learning for Computer Scientists and Data Analysts, 81–162. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-96756-7_3.
Texto completo da fonteYang, Qihan, Fan Feng e Rosa H. M. Chan. "A Benchmark and Empirical Analysis for Replay Strategies in Continual Learning". In Continual Semi-Supervised Learning, 75–90. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17587-9_6.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Analyse supervisée"
Stieģele, Dace, e Ilze Miķelsone. "Pedagogical Supervision in the Higher Education Study Process". In 80th International Scientific Conference of the University of Latvia. University of Latvia Press, 2022. http://dx.doi.org/10.22364/htqe.2022.36.
Texto completo da fonte"A Project Management Perspective of PhD Supervision Process – Towards Effective and Efficient Model [Abstract]". In InSITE 2019: Informing Science + IT Education Conferences: Jerusalem. Informing Science Institute, 2019. http://dx.doi.org/10.28945/4349.
Texto completo da fonteRachmawati, Rika, Didin Saepudin e Taufik Zulfikar. "KOMUNIKASI ORGANISASI, SUPERVISI, DAN LINGKUNGAN KERJA MENINGKATKAN KEPUASAN KERJA PEGAWAI DINAS PENDIDIKAN DAN KEBUDAYAAN SUBANG". In Seminar Sosial Politik, Bisnis, Akuntansi dan Teknik (SoBAT) ke-3. LPPM USB YPKP, 2021. http://dx.doi.org/10.32897/sobat3.2021.4.
Texto completo da fonteBihler, Manuel, Jiachen Zhou e Michael Heizmann. "Semi-supervised methods for CNN based classification of multispectral imagery". In OCM 2023 - 6th International Conference on Optical Characterization of Materials, March 22nd – 23rd, 2023, Karlsruhe, Germany : Conference Proceedings. KIT Scientific Publishing, 2023. http://dx.doi.org/10.58895/ksp/1000155014-4.
Texto completo da fonteArrieta, José Miguel, Oscar Julian Perdomo Charry e Fabio A. González. "Deep semi-supervised and self-supervised learning for diabetic retinopathy detection". In 18th International Symposium on Medical Information Processing and Analysis (SIPAIM 2022), editado por Marius G. Linguraru, Letícia Rittner, Natasha Lepore, Eduardo Romero Castro, Jorge Brieva e Pamela Guevara. SPIE, 2023. http://dx.doi.org/10.1117/12.2669723.
Texto completo da fonteLEMPA, P. "Analysis of Neural Network Training Algorithms for Implementation of the Prescriptive Maintenance Strategy". In Terotechnology XII. Materials Research Forum LLC, 2022. http://dx.doi.org/10.21741/9781644902059-41.
Texto completo da fonteMing Yang e Xing-Mei Yuan. "Structured Semi-supervised Discriminant Analysis". In 2009 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR). IEEE, 2009. http://dx.doi.org/10.1109/icwapr.2009.5207467.
Texto completo da fonteLv, Qiwen, Lei Wang, Hanyu Hong, Shuwei Zhao e Lingmu Peng. "Semi-supervised polarimetric SAR images classification based on FixMatch". In Multispectral Image Processing and Analysis. SPIE, 2024. http://dx.doi.org/10.1117/12.2692789.
Texto completo da fonteKasozi, Joseph Amooti, e Mmabaledi Seeletso. "Developing an Indigenous Graduate Research Supervision Culture in an Open and Distance e-Learning Environment. Lessons from an ODeL Programme". In Tenth Pan-Commonwealth Forum on Open Learning. Commonwealth of Learning, 2022. http://dx.doi.org/10.56059/pcf10.425.
Texto completo da fonteBall, Gregory R., e Sargur N. Srihari. "Semi-supervised Learning for Handwriting Recognition". In 2009 10th International Conference on Document Analysis and Recognition. IEEE, 2009. http://dx.doi.org/10.1109/icdar.2009.249.
Texto completo da fonteRelatórios de organizações sobre o assunto "Analyse supervisée"
Estrella, Tony, Carla Alfonso, Lluis Capdevila e Josep-Maria Losilla. Machine learning for the analysis of healthy lifestyle data: a scoping review protocol. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, março de 2023. http://dx.doi.org/10.37766/inplasy2023.3.0065.
Texto completo da fonteSpirling, Arthur. Text Analysis: Text as Data with R. Instats Inc., 2022. http://dx.doi.org/10.61700/a52fcasdqm1du469.
Texto completo da fonteSpirling, Arthur. Text Analysis: Text as Data with R. Instats Inc., 2022. http://dx.doi.org/10.61700/lolq2hyg9sn6d469.
Texto completo da fonteRojas-Suárez, Liliana, e Steven R. Weisbrod. Towards an Effective Regulatory and Supervisory Framework for Latin America. Inter-American Development Bank, setembro de 1996. http://dx.doi.org/10.18235/0011587.
Texto completo da fonteTian, Cong, Jianlong Shu, Wenhui Shao, Zhengxin Zhou, Huayang Guo e Jingang Wang. The efficacy and safety of IL Inhibitors, TNF-α Inhibitors, and JAK Inhibitor on ankylosing spondylitis: A Bayesian network meta-analysis of a “randomized, double-blind, placebo-controlled” trials. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, setembro de 2022. http://dx.doi.org/10.37766/inplasy2022.9.0117.
Texto completo da fonteCarrol. PR-214-05502-R01 Application of Fatigue Analysis Procedures Using Pipeline SCADA Data. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), fevereiro de 2007. http://dx.doi.org/10.55274/r0011248.
Texto completo da fonteBalzarotti, Verónica, e Andrew Powell. Capital Requirements for Latin American Banks in Relation to their Market Risks: The Relevance of the Basle 1996 Amendment to Latin America. Inter-American Development Bank, janeiro de 1997. http://dx.doi.org/10.18235/0011539.
Texto completo da fonteAtuesta, Laura, María Aulet, Yuri Soares, Mayra Ruiz, Santiago Ramirez, Diana Rangel e Chloe Fevre. The Implementation Challenge: Lessons From Five Citizen Security Projects. Inter-American Development Bank, junho de 2013. http://dx.doi.org/10.18235/0010574.
Texto completo da fonteEngel, Bernard, Yael Edan, James Simon, Hanoch Pasternak e Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, julho de 1996. http://dx.doi.org/10.32747/1996.7613033.bard.
Texto completo da fonteSECOND-ORDER ANALYSIS OF BEAM-COLUMNS BY MACHINE LEARNING-BASED STRUCTURAL ANALYSIS THROUGH PHYSICS-INFORMED NEURAL NETWORKS. The Hong Kong Institute of Steel Construction, dezembro de 2023. http://dx.doi.org/10.18057/ijasc.2023.19.4.10.
Texto completo da fonte