Academic literature on the topic 'Analyse supervisée'
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Journal articles on the topic "Analyse supervisée":
Berriche, Amira, Dominique Crié, and Michel Calciu. "Une Approche Computationnelle Ancrée : Étude de cas des tweets du challenge #Movember en prévention de santé masculine." Décisions Marketing N° 112, no. 4 (January 25, 2024): 79–103. http://dx.doi.org/10.3917/dm.112.0079.
Glendenning, Jonathan. "Espace disciplinaire et normativité sociale contemporaine." Perspectives étatiques 28, no. 1 (March 15, 2017): 195–210. http://dx.doi.org/10.7202/1039181ar.
Idrissa, Ali, Amani Abdou, Barmo Soukaradji, Ibrahim Biga, and 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, no. 3 (August 24, 2023): 1033–47. http://dx.doi.org/10.4314/ijbcs.v17i3.22.
Juge, 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 (December 2023): A27—A28. http://dx.doi.org/10.1016/j.rhum.2023.10.040.
Tegno Nguekam, Eric Wilson, Salomon C. Nguemhe Fils, Joachim Etouna, and 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, no. 222 (November 26, 2020): 31–41. http://dx.doi.org/10.52638/rfpt.2020.434.
Ganachaud, Clément, Ludovic Seifert, and 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, no. 3 (January 17, 2024): 97–108. http://dx.doi.org/10.3917/sta.141.0097.
Testa, D., N. Jourde-Chiche, J. Mancini, P. Varriale, V. Morisseau, L. Radoszycki, and 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 (June 2021): A85. http://dx.doi.org/10.1016/j.revmed.2021.03.306.
Törnquist, Anna, Sarah Rakovshik, Jan Carlsson, and 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, no. 3 (September 14, 2017): 302–17. http://dx.doi.org/10.1017/s1352465817000558.
Bencherif, Kada, and 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, no. 215 (August 16, 2017): 3–11. http://dx.doi.org/10.52638/rfpt.2017.360.
Wils, Thierry, and Aziz Rhnima. "Taxonomie des conflits entre le travail et la famille : une analyse multidimensionnelle à l’aide de cartes auto-organisatrices." Articles 70, no. 3 (October 5, 2015): 432–56. http://dx.doi.org/10.7202/1033405ar.
Dissertations / Theses on the topic "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.
Goubet, Étienne. "Contrôle non destructif par analyse supervisée d'images 3D ultrasonores." Cachan, Ecole normale supérieure, 1999. http://www.theses.fr/1999DENS0011.
Huck, Alexis. "Analyse non-supervisée d’images hyperspectrales : démixage linéaire et détection d’anomalies." Aix-Marseille 3, 2009. http://www.theses.fr/2009AIX30036.
This 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.
Faucheux, Cyrille. "Segmentation supervisée d'images texturées par régularisation de graphes." Thesis, Tours, 2013. http://www.theses.fr/2013TOUR4050/document.
In 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.
This 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.
This 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.
Conan-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.
Vandewalle, 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.
Books on the topic "Analyse supervisée":
Catoni, Olivier. PAC-Bayesian supervised classification: The thermodynamics of statistical learning. Beachwood, Ohio: Institute of Mathematical Statistics, 2007.
Zutter, 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.
Anikin, Valeriy, and Boris Poyzner. To the dissertation dissertation: the semantic aspect. ru: INFRA-M Academic Publishing LLC., 2024. http://dx.doi.org/10.12737/1909143.
Corporation, National Learning. Workforce Development Analyst/Supervisor: Passbooks Study Guide. National Learning Corporation, 2016.
Singh, Dalvinder. European Cross-Border Banking and Banking Supervision. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198844754.001.0001.
Partially Supervised Learning. Springer-Verlag Berlin and Heidelberg GmbH &, 2012.
Applications Of Supervised And Unsupervised Ensemble Methods. Springer, 2009.
Baillo, Amparo, Antonio Cuevas, and Ricardo Fraiman. Classification methods for functional data. Edited by Frédéric Ferraty and Yves Romain. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199568444.013.10.
Rodrigo, Olivares-Caminal, Douglas John, Guynn Randall, Kornberg Alan, Paterson Sarah, and 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.
Varol, Ozan O. Golden Parachutes. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190626013.003.0017.
Book chapters on the topic "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.
Verdhan, 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.
Aggarwal, 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.
Aggarwal, 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.
Mark, Howard. "Supervised Methods." In Handbook of Near-Infrared Analysis, 211–33. 4th ed. Fourth edition. | Boca Raton : Taylor and Francis, 2021. |: CRC Press, 2021. http://dx.doi.org/10.1201/b22513-15.
Riese, Felix M., and 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.
M. Bagirov, Adil, Napsu Karmitsa, and 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.
Marron, J. S., and 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.
Rafatirad, Setareh, Houman Homayoun, Zhiqian Chen, and 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.
Yang, Qihan, Fan Feng, and 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.
Conference papers on the topic "Analyse supervisée":
Stieģele, Dace, and 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.
"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.
Rachmawati, Rika, Didin Saepudin, and 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.
Bihler, Manuel, Jiachen Zhou, and 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.
Arrieta, José Miguel, Oscar Julian Perdomo Charry, and 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), edited by Marius G. Linguraru, Letícia Rittner, Natasha Lepore, Eduardo Romero Castro, Jorge Brieva, and Pamela Guevara. SPIE, 2023. http://dx.doi.org/10.1117/12.2669723.
LEMPA, 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.
Ming Yang and 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.
Lv, Qiwen, Lei Wang, Hanyu Hong, Shuwei Zhao, and 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.
Kasozi, Joseph Amooti, and 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.
Ball, Gregory R., and 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.
Reports on the topic "Analyse supervisée":
Estrella, Tony, Carla Alfonso, Lluis Capdevila, and 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, March 2023. http://dx.doi.org/10.37766/inplasy2023.3.0065.
Spirling, Arthur. Text Analysis: Text as Data with R. Instats Inc., 2022. http://dx.doi.org/10.61700/a52fcasdqm1du469.
Spirling, Arthur. Text Analysis: Text as Data with R. Instats Inc., 2022. http://dx.doi.org/10.61700/lolq2hyg9sn6d469.
Rojas-Suárez, Liliana, and Steven R. Weisbrod. Towards an Effective Regulatory and Supervisory Framework for Latin America. Inter-American Development Bank, September 1996. http://dx.doi.org/10.18235/0011587.
Tian, Cong, Jianlong Shu, Wenhui Shao, Zhengxin Zhou, Huayang Guo, and 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, September 2022. http://dx.doi.org/10.37766/inplasy2022.9.0117.
Carrol. PR-214-05502-R01 Application of Fatigue Analysis Procedures Using Pipeline SCADA Data. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), February 2007. http://dx.doi.org/10.55274/r0011248.
Balzarotti, Verónica, and 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, January 1997. http://dx.doi.org/10.18235/0011539.
Atuesta, Laura, María Aulet, Yuri Soares, Mayra Ruiz, Santiago Ramirez, Diana Rangel, and Chloe Fevre. The Implementation Challenge: Lessons From Five Citizen Security Projects. Inter-American Development Bank, June 2013. http://dx.doi.org/10.18235/0010574.
Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, July 1996. http://dx.doi.org/10.32747/1996.7613033.bard.
SECOND-ORDER ANALYSIS OF BEAM-COLUMNS BY MACHINE LEARNING-BASED STRUCTURAL ANALYSIS THROUGH PHYSICS-INFORMED NEURAL NETWORKS. The Hong Kong Institute of Steel Construction, December 2023. http://dx.doi.org/10.18057/ijasc.2023.19.4.10.