I. Bloch, B. Collin, F. Ealet, C. Garbay, J. Le-cadre et al., Fusion d'informations en traitement du signal et des images, 2003.

E. Bossé, A. Jousselme, and P. Maupin, Knowledge, uncertainty and belief in information fusion and situation analysis. In Data Fusion for Situation Monitoring , Incident Detection, Alert and Response Management, Nato Science Series III, vol.198, pp.61-80, 2005.

R. L. Ackoff, From data to wisdom, Journal of Applied Systems Analysis, vol.16, pp.3-9, 1989.

P. E. Bierly, E. H. Kessle, and E. W. Christensen, Organizational learning, knowledge and wisdom, Journal of Organizational Change Management, vol.13, issue.6, pp.595-618, 2000.
DOI : 10.1108/09534810010378605

C. Rouchouze, Fusion de données : exemple défense et axes de recherche, Traitement du Signal, vol.11, issue.6, pp.459-464, 1994.

D. Dubois and H. Prade, La problématique scientifique du traitement de l'information . Information -Interaction -Intelligence (I3), 2001.

F. E. White, Data Fusion Lexicon Joint Directors of Laboratories, Technical Panel for C3, Data Fusion Subpanel, Naval Ocean Systems Center, 1987.

J. Llinas, Toward the utilization of certain elements of ai technology for multi sensor data fusion Application of artificial intelligence to command and control systems, 1987.

H. F. Durrant-whyte, Integration, coordination and control of multi-sensor robot systems, 1988.
DOI : 10.1007/978-1-4613-2009-8

M. A. Abidi and R. C. Gonzalez, Data fusion in robotics and machine intelligence, 1992.

D. L. Hall, Mathematical Techniques in Multisensor Data Fusion, 1992.

M. Kokar and K. Kim, Preface to the special section on data fusion: Architectures and issues, Control Engineering Practice, vol.2, issue.5, pp.803-809, 1994.
DOI : 10.1016/0967-0661(94)90345-X

R. Malhotra, Temporal considerations in sensor management, Proceedings of the IEEE 1995 National Aerospace and Electronics Conference. NAECON 1995, pp.86-93, 1995.
DOI : 10.1109/NAECON.1995.521917

D. L. Hall and J. Llinas, An introduction to multisensor data fusion, Proceedings of the IEEE, vol.85, issue.1, pp.6-23, 1997.
DOI : 10.1109/5.554205

S. Paradis, B. A. Chalmers, R. Carling, and P. Bergeron, Toward a generic model for situation and threat assessment, SPIE, vol.3080, pp.171-182, 1997.

L. Wald, A European proposal for terms of reference in data fusion In International Archives of Photogrammetry and Remote Sensing Commission VII Symposium Resource and Environmental Monitoring, pp.651-654, 1998.

B. V. Dasarathy, Information Fusion ??? what, where, why, when, and how?, Information Fusion, vol.2, issue.2, pp.75-76, 2001.
DOI : 10.1016/S1566-2535(01)00032-X

D. L. Hall and J. Llinas, Handbook of Multisensor Data Fusion, 2001.

F. Mastrogiovanni, A. Sgorbissa, and R. Zaccaria, A distributed architecture for symbolic data fusion, International Joint Conference on Artificial Intelligence IJCAI'07, pp.2153-2158, 2007.

B. V. Dasarathy, Sensor fusion potential exploitation-innovative architectures and illustrative applications, Proceedings of the IEEE, vol.85, issue.1, pp.24-38, 1997.
DOI : 10.1109/5.554206

M. Mangolini, Apport de la fusion d'images satellitaires multicapteurs au niveau pixels en télédétection et photo-interprétation, 1994.

R. Reynaud and S. Bouaziz, Architecture de systémes multicapteurs Traitement du signal (Méthodologie de la gestion intelligente des senseurs, pp.393-405, 2005.

M. Bedworth and J. O-'brien, The Omnibus model: a new model of data fusion?, IEEE Aerospace and Electronics Systems Magazine, pp.30-36, 2000.
DOI : 10.1109/62.839632

M. E. Liggins, C. Y. Chong, I. Kadar, M. G. Alford, V. Vannicola et al., Distributed Fusion Architectures and Algorithms for Target Tracking, Proceedings of the IEEE, vol.85, issue.1, pp.95-107, 1997.
DOI : 10.1109/JPROC.1997.554211

L. Wald, Data Fusion Definitions and Architectures Fusion of Images of Different Spatial Resolutions, 2002.
URL : https://hal.archives-ouvertes.fr/hal-00464703

M. Kokar and K. Kim, Review of multisensor data fusion architectures and techniques, Proceedings of 8th IEEE International Symposium on Intelligent Control, pp.261-266, 1993.
DOI : 10.1109/ISIC.1993.397703

J. Esteban, A. Starr, R. Willetts, P. Hannah, and P. Bryanston-cross, A Review of data fusion models and architectures: towards engineering guidelines, Neural Computing and Applications, vol.6, issue.6, pp.273-281, 2005.
DOI : 10.1007/s00521-004-0463-7

P. Blasch and S. Plano, <title>JDL level 5 fusion model: user refinement issues and applications in group tracking</title>, Signal Processing, Sensor Fusion, and Target Recognition XI, 2002.
DOI : 10.1117/12.477612

A. N. Steinberg, C. L. Bowman, and F. E. White, Revisions to the JDL data fusion model, Storage and Retrieval for Image and Video Databases, 1999.

J. Llinas, C. Bowman, G. Rogova, A. Steinberg, E. Waltz et al., Revisiting the JDL data fusion model II, Proceedings of the Seventh International Conference on Information Fusion ICIF, pp.1218-1230, 2004.

C. J. Harris, A. Bailey, and T. J. Dodd, Multi-sensor data fusion in defence and aerospace, Aeronautical Journal, vol.102, pp.229-244, 1015.

J. Boyd, A Discourse on Winning and Losing, 1987.

F. E. White, A model for data fusion, Proceedings of the First National Symposium on Sensor Fusion, 1998.

L. Valet, Un système flou de fusion coopérative application au traitement d'images naturelles, 2001.

L. Trasoudaine, P. Checchin, J. Alizon, F. Collange, and J. Gallice, Gestion intelligente de capteurs et fusion multisensorielle pour la détection et le suivi d'obstacles sur route, pp.127-142, 1996.

P. K. Varshney, Scanning the issue, pp.3-5, 1997.

S. R. Julien, Systèmes coopératifs de fusion explicitant les dépendances entre les informations : application à l'interprétaion d'images tomographiques 3D et à la sélection de films d'animation, 2008.

L. Valet, G. Mauris, P. Bolon, and N. Keskes, A fuzzy rule-based interactive fusion system for seismic data analysis, Information Fusion, vol.4, issue.2, pp.123-133, 2003.
DOI : 10.1016/S1566-2535(03)00002-2

URL : https://hal.archives-ouvertes.fr/hal-00514200

V. Bombardier, C. Mazaud, P. Lhoste, and R. Vogrig, Contribution of fuzzy reasoning method to knowledge integration in a defect recognition system, Computers in Industry, vol.58, issue.4, pp.355-366, 2007.
DOI : 10.1016/j.compind.2006.07.006

URL : https://hal.archives-ouvertes.fr/hal-00120322

N. M. Wanas, D. A. Rozita, and K. S. Mohamed, Adaptive fusion and co-operative training for classifier ensembles, Pattern Recognition, vol.39, issue.9, pp.1781-1794, 2006.
DOI : 10.1016/j.patcog.2006.02.003

B. V. Dasarathy, Elucidative fusion systems ??? an exposition, Information Fusion, vol.1, issue.1, pp.5-15, 2000.
DOI : 10.1016/S1566-2535(00)00006-3

A. Bastière, Methods for multisensor classification of airborne targets integrating evidence theory, Aerospace Science and Technology, vol.2, issue.6, pp.401-411, 1998.
DOI : 10.1016/S1270-9638(99)80028-5

M. Kam, C. Rorres, W. Chang, and X. Zhu, Performance and geometric interpretation for decision fusion with memory, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, vol.29, issue.1, pp.52-62, 1999.
DOI : 10.1109/3468.736360

N. G. Brannon, J. E. Seiffertt, T. J. Draelos, D. C. Wunsch, and I. , Coordinated machine learning and decision support for situation awareness, Neural Networks, vol.22, issue.3, pp.316-325, 2009.
DOI : 10.1016/j.neunet.2009.03.013

J. Desachy, L. Roux, and E. Zahzah, Numeric and symbolic data fusion: A soft computing approach to remote sensing images analysis, Pattern Recognition Letters, vol.17, issue.13, pp.1361-1378, 1996.
DOI : 10.1016/S0167-8655(96)00093-1

N. Milisavljevic, Analysis and fusion in the theory of Belief function of multi-sensor data for humanitarian mine detection, 2008.

C. Ciofolo and C. Barillot, Atlas-based segmentation of 3D cerebral structures with competitive level sets and fuzzy control, Medical Image Analysis, vol.13, issue.3, pp.456-470, 2009.
DOI : 10.1016/j.media.2009.02.008

URL : https://hal.archives-ouvertes.fr/inserm-00443873

C. Ciofolo and C. Barillot, Brain Segmentation with Competitive Level Sets and Fuzzy Control, Information Processing in Medical Imaging, pp.489-517, 2005.
DOI : 10.1007/11505730_28

URL : https://hal.archives-ouvertes.fr/inserm-00137473

J. L. Foo, G. Miyano, T. Lobe, and E. Winer, Three-dimensional segmentation of tumors from CT image data using an adaptive fuzzy system, Computers in Biology and Medicine, vol.39, issue.10, pp.869-878, 2009.
DOI : 10.1016/j.compbiomed.2009.06.013

P. Jannin, C. Grova, and B. Gibaud, Fusion de donn??es en imagerie m??dicale: revue m??thodologique bas??e sur le contexte clinique, ITBM-RBM, vol.22, issue.4, pp.196-215, 2001.
DOI : 10.1016/S1297-9562(01)90049-X

W. Dou, S. Ruan, Y. Chen, D. Bloyet, and J. Constans, A framework of fuzzy information fusion for the segmentation of brain tumor tissues on MR images, Image and Vision Computing, vol.25, issue.2, pp.164-171, 2007.
DOI : 10.1016/j.imavis.2006.01.025

URL : https://hal.archives-ouvertes.fr/hal-00673700

K. J. Worsley and K. J. Friston, Analysis of fMRI Time-Series Revisited???Again, NeuroImage, vol.2, issue.3, pp.173-181, 1995.
DOI : 10.1006/nimg.1995.1023

G. Niu and B. Yang, Intelligent condition monitoring and prognostics system based on data-fusion strategy, Expert Systems with Applications, vol.37, issue.12, pp.8831-8840, 2010.
DOI : 10.1016/j.eswa.2010.06.014

C. S. Wu, J. Xu, and L. Wu, A diagnostic expert system for weld defects, Engineering Applications of Artificial Intelligence, vol.4, issue.1, pp.65-69, 1991.
DOI : 10.1016/0952-1976(91)90070-M

M. Mitchell, Complex systems: Network thinking, Artificial Intelligence, vol.170, issue.18, pp.1194-1212, 2006.
DOI : 10.1016/j.artint.2006.10.002

Y. J. Zhang, A survey on evaluation methods for image segmentation, Pattern Recognition, vol.29, issue.8, pp.1335-1346, 1996.
DOI : 10.1016/0031-3203(95)00169-7

A. Hafiane, S. Chabrier, C. Rosenberger, and H. Laurent, A New Supervised Evaluation Criterion for Region Based Segmentation Methods, Advanced Concepts for Intelligent Vision Systems ACIVS07, pp.439-448, 2007.
DOI : 10.1007/978-3-540-74607-2_40

W. Pedrycz, L. Yang, and M. Ha, On the fundamental convergence in the (C) mean in problems of information fusion, Journal of Mathematical Analysis and Applications, vol.358, issue.2, pp.203-222, 2009.
DOI : 10.1016/j.jmaa.2009.04.037

J. Dubus, Mesure par analyse d'image analyse multirésolution et psychovisuelle, Traités des Techniques de l'Ingénieur, pp.1-20, 1998.

F. Laporterie-déjean, H. De-boissezon, G. Flouzat, and M. Lefèvre-fonollosa, Thematic and statistical evaluations of five panchromatic/multispectral fusion methods on simulated PLEIADES-HR images, Information Fusion, vol.6, issue.3, pp.193-212, 2005.
DOI : 10.1016/j.inffus.2004.06.006

H. Chen and P. K. Varshney, A human perception inspired quality metric for image fusion based on regional information, Information Fusion, vol.8, issue.2, pp.193-207, 2007.
DOI : 10.1016/j.inffus.2005.10.001

Y. Chen and R. S. Blum, A new automated quality assessment algorithm for image fusion, Image and Vision Computing, vol.27, issue.10, pp.1421-1432, 2009.
DOI : 10.1016/j.imavis.2007.12.002

V. Petrovic, Subjective tests for image fusion evaluation and objective metric validation, Information Fusion, vol.8, issue.2, pp.208-216, 2007.
DOI : 10.1016/j.inffus.2005.05.001

A. Toet and E. M. Franken, Perceptual evaluation of different image fusion schemes, Displays, vol.24, issue.1, pp.25-37, 2003.
DOI : 10.1016/S0141-9382(02)00069-0

G. Qu, D. Zhang, and P. Yan, Information measure for performance of image fusion, Electronics Letters, vol.38, issue.7, pp.313-315, 2002.
DOI : 10.1049/el:20020212

C. S. Xydeas and V. Petrovic, Objective image fusion performance measure, Electronics Letters, vol.36, issue.4, pp.308-309, 2000.
DOI : 10.1049/el:20000267

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.332.7913

Z. Wang and A. C. Bovik, A universal image quality index, International Journal of Signal Processing, vol.9, issue.3, pp.81-84, 2002.

A. Lamallem, L. Valet, and D. Coquin, Performance Evaluation of a Fusion System Devoted to Image Interpretation, 13th International Conference on Information Processing and Management of Uncertainty IPMU, pp.464-473, 2010.
DOI : 10.1007/978-3-642-14049-5_48

URL : https://hal.archives-ouvertes.fr/hal-00514247

F. Bujor, Extraction -fusion d'informations en imagerie radar multi-temporelle, 2004.

L. Vinet, Segmentation et mise en correspondance de régions de paires d'images stéréoscopiques, 1991.

D. R. Martin, An Empirical Approach to Grouping and Segmentation, 2003.

W. A. Yasnoff, J. K. Mui, and J. W. Bacus, Error measures for scene segmentation, Pattern Recognition, vol.9, issue.4, pp.217-231, 1977.
DOI : 10.1016/0031-3203(77)90006-1

A. J. Baddeley, An error metric for binary images, Proceedings of the second International Workshop on Robust Computer Vision : Quality of Vision Algorithms, pp.59-78, 1992.

S. X. Yu and J. Shi, Segmentation given partial grouping constraints, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.2, pp.173-183, 2004.
DOI : 10.1109/TPAMI.2004.1262179

S. Chabrier, Contribution à l'évaluation de performances en segmentation d'images, 2004.

H. Zhang, J. E. Fritts, and S. A. Goldman, Image segmentation evaluation: A survey of unsupervised methods, Computer Vision and Image Understanding, vol.110, issue.2, pp.260-280, 2008.
DOI : 10.1016/j.cviu.2007.08.003

F. Huet and S. Philipp, Fusion of images interpreted by a new fuzzy classifier, Pattern Analysis and Applications, vol.26, issue.1, pp.231-247, 1998.
DOI : 10.1007/BF01234770

H. Mine and K. Ohno, Decomposition of mathematical programming problems by dynamic programming and its application to block-diagonal geometric programs, Journal of Mathematical Analysis and Applications, vol.32, issue.2, pp.370-385, 1970.
DOI : 10.1016/0022-247X(70)90303-3

L. V. Bertalanffy, General System theory : Foundations , Development , Applications. George Braziller, 1976.

K. E. Boulding, The Image : knowledge in life and society. The University of, 1956.
DOI : 10.3998/mpub.6607

W. R. Ashby, An introduction to cybernetics, 1957.

J. L. Le-moigne, La modélisation des systèmes complexes, 1990.

H. Crowther-heyck, Herbert Simon and the GSIA: Building an interdisciplinary community, Journal of the History of the Behavioral Sciences, vol.75, issue.4, pp.311-334, 2006.
DOI : 10.1002/jhbs.20189

J. and D. Rosnay, Le macroscope : vers une vision globale, 1975.

E. Morin, La méthode Tome 1, La nature de la nature, Editions du Seuil, 1977.

H. Mintzberg and J. B. Quinn, The strategy process : concepts, contexts, cases, 1996.

H. A. Simon, Models of bounded rationality, 1982.

V. Clivillé, Approche systémique et méthode multicritère pour la définition d'un système d'indicateurs de performance, 2004.

P. J. Hancock, R. J. Baddeley, and L. S. Smith, The principal components of natural images, Network: Computation in Neural Systems, vol.3, issue.1, pp.61-70, 1992.
DOI : 10.1088/0954-898X_3_1_008

R. M. Haralick and L. G. Shapiro, Computer and robot vision, 1992.

M. Grabisch and M. Sugeno, Multi-attribute classification using fuzzy integral, [1992 Proceedings] IEEE International Conference on Fuzzy Systems, pp.47-54, 1992.
DOI : 10.1109/FUZZY.1992.258678

M. Grabisch and J. Nicolas, Classification by fuzzy integral : Performance and tests. Fuzzy Sets and Systems, pp.255-271, 1994.

T. Chaira and A. K. Ray, Fuzzy measures for color image retrieval. Fuzzy Sets and Systems, pp.545-560, 2005.

M. Grabisch, The application of fuzzy integrals in multicriteria decision making, European Journal of Operational Research, vol.89, issue.3, pp.445-456, 1996.
DOI : 10.1016/0377-2217(95)00176-X

S. Jullien, L. Valet, G. Mauris, P. Bolon, and S. Teyssier, An Attribute Fusion System Based on the Choquet Integral to Evaluate the Quality of Composite Parts, IEEE Transactions on Instrumentation and Measurement, vol.57, issue.4, pp.755-762, 2008.
DOI : 10.1109/TIM.2007.913719

URL : https://hal.archives-ouvertes.fr/hal-00447475

G. E. Box, W. G. Hunter, and J. S. Hunter, Statistics for Experimenters. deuxième édition, 2005.

A. Lamallem, D. Coquin, and L. Valet, Aggregation evaluation of a fusion system devoted to image interpretation, 2010 13th International Conference on Information Fusion, 2010.
DOI : 10.1109/ICIF.2010.5712094

URL : https://hal.archives-ouvertes.fr/hal-00514250

Y. Rubner, C. Tomasi, and L. Guibas, The earth mover's distance as a metric for image retrieval, International Journal of Computer Vision, vol.40, issue.2, pp.99-121, 2000.
DOI : 10.1023/A:1026543900054

M. J. Swain and D. H. Ballard, Color indexing, International Journal of Computer Vision, vol.31, issue.1, pp.11-32, 1991.
DOI : 10.1007/BF00130487

M. Stricker and M. Orengo, Similarity of color images In Storage and Retrieval for Image and Video Databases, pp.381-392, 1995.

L. Lee, Measures of distributional similarity, Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics -, pp.25-32, 1999.
DOI : 10.3115/1034678.1034693

O. Pele and M. Werman, The Quadratic-Chi Histogram Distance Family, European Conference on Computer Vision, 2010.
DOI : 10.1007/978-3-642-15552-9_54

W. Niblack, R. Barber, W. Equitz, M. Flickner, E. H. Glasman et al., <title>QBIC project: querying images by content, using color, texture, and shape</title>, Storage and Retrieval for Image and Video Databases, pp.173-187, 1993.
DOI : 10.1117/12.143648

M. Werman, S. Peleg, and A. Rosenfeld, A distance metric for multidimensional histograms, Computer Vision, Graphics, and Image Processing, pp.328-336, 1985.
DOI : 10.1016/0734-189X(85)90055-6

C. T. Yossi-rubner and L. J. Guibas, A metric for distributions with applications to image database, International Conference on Computer Vision IEEE, pp.59-66, 1998.

H. Ling and K. Okada, An Efficient Earth Mover's Distance Algorithm for Robust Histogram Comparison, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, issue.5, pp.840-853, 2007.
DOI : 10.1109/TPAMI.2007.1058

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.127.854

A. Lamallem, L. Valet, and D. Coquin, A separability index based on earth mover's distance for local evaluation of fusion systems, 2010 International Symposium on Optomechatronic Technologies, 2010.
DOI : 10.1109/ISOT.2010.5687361

A. Lamallem, L. Valet, and D. Coquin, Towards the supervision of a fusion system for 3D image interpretation, 2011 11th International Conference on Intelligent Systems Design and Applications, p.page cdrom, 2011.
DOI : 10.1109/ISDA.2011.6121734

URL : https://hal.archives-ouvertes.fr/hal-00621093

G. Mauris, Representing and Approximating Symmetric and Asymmetric Probability Coverage Intervals by Possibility Distributions, IEEE Transactions on Instrumentation and Measurement, vol.58, issue.1, pp.41-45, 2009.
DOI : 10.1109/TIM.2008.2004980

URL : https://hal.archives-ouvertes.fr/hal-00426781

S. Destercke, D. Dubois, and E. Chojnacki, Possibilistic Information Fusion Using Maximal Coherent Subsets, IEEE Transactions on Fuzzy Systems, vol.17, issue.1, pp.79-92, 2009.
DOI : 10.1109/TFUZZ.2008.2005731

URL : https://hal.archives-ouvertes.fr/irsn-00196483

A. , D. Luca, and S. Termini, A definition of a nonprobabilistic entropy in the setting of fuzzy sets theory, Information and Control, vol.20, issue.4, pp.301-312, 1972.

L. Valet, B. S. De-lima, and A. G. Evsukoff, A Genetic-Algorithm-Based Fusion System Optimization for 3D Image Interpretation, 15th Iberoamerican Congress on Pattern Recognition, CIARP2010, pp.338-345
DOI : 10.1007/978-3-642-16687-7_46

URL : https://hal.archives-ouvertes.fr/hal-00517357

J. Holland, Adaptation in Natural and Artificial Systems : An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, 1992.

O. Guenounou, Méthodologie de conception de contrôleurs intelligents par l'approche génétique-application à un bioprocédé, 2009.

J. J. Grefenstette, A user's guide to genesis 5.0, Navy Centre for Applied Research in Artificial Intelligence, 1990.

M. Beckmann, L. Valet, B. S. De, and . Lima, Choquet Integral Parameter Optimization for a Fusion System Devoted to Image Interpretation, 14th International Conference on Information Processing and Management of Uncertainty IPMU, 2012.
DOI : 10.1007/978-3-642-31709-5_54

URL : https://hal.archives-ouvertes.fr/hal-00724678

S. Singh, M. Singh, and M. Markou, Feature selection for face recognition based on data partitioning, Object recognition supported by user interaction for service robots, pp.680-683, 2002.
DOI : 10.1109/ICPR.2002.1044845

K. Fukunaga, Statistical pattern recognition : Second edition, 1990.

A. Lamallem, L. Valet, and D. Coquin, Local Evaluation of a Fusion System for 3-D Tomographic Image Interpretation, International Journal of Optomechatronics, vol.5666, issue.4, pp.362-378, 2010.
DOI : 10.1016/0031-3203(95)00169-7

URL : https://hal.archives-ouvertes.fr/hal-00527233

A. Lamallem, L. Valet, D. Coquin, B. S. De-lima, and S. Galichet, Symbolic evaluation of a fusion system devoted to 3D image interpretation, 32th Iberian Latin American Congress on Computational Methods in Engineering (CILAMCE), Ouro Preto, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00724673

A. Lamallem, L. Valet, and D. Coquin, Local Evaluation of a Fusion System for 3-D Tomographic Image Interpretation, International Journal of Optomechatronics, vol.5666, issue.4, pp.362-378, 2010.
DOI : 10.1016/0031-3203(95)00169-7

URL : https://hal.archives-ouvertes.fr/hal-00527233

A. Lamallem, L. Valet, and D. , Coquin Towards the Supervision of a Fusion System for 3D Image Interpretation, IEEE International Conference on Intelligent Systems Design and Applications (ISDA)

A. Lamallem, L. Valet, D. Coquin, B. S. De-lima, and S. Galichet, Symbolic evaluation of a fusion system devoted to 3D image interpretation
URL : https://hal.archives-ouvertes.fr/hal-00724673

A. Lamallem, D. Valet, and . Coquin, A separability index based on earth mover's distance for local evaluation of fusion systems, 2010 International Symposium on Optomechatronic Technologies
DOI : 10.1109/ISOT.2010.5687361

A. Lamallem, D. Coquin, and L. Valet, Aggregation evaluation of a fusion system devoted to image interpretation, 2010 13th International Conference on Information Fusion
DOI : 10.1109/ICIF.2010.5712094

URL : https://hal.archives-ouvertes.fr/hal-00514250

A. Lamallem, L. Valet, and D. Coquin, Performance Evaluation of a Fusion System Devoted to Image Interpretation, International Conference on Information Processing
DOI : 10.1007/978-3-642-14049-5_48

URL : https://hal.archives-ouvertes.fr/hal-00514247

.. Le-modèle-en-cascade, Waterfall model), p.17