Academic literature on the topic 'Algorithmes de fusion'
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Journal articles on the topic "Algorithmes de fusion"
Thomson, Ashlee J., Jacqueline A. Rehn, Susan L. Heatley, Laura N. Eadie, Elyse C. Page, Caitlin Schutz, Barbara J. McClure, et al. "Reproducible Bioinformatics Analysis Workflows for Detecting IGH Gene Fusions in B-Cell Acute Lymphoblastic Leukaemia Patients." Cancers 15, no. 19 (September 26, 2023): 4731. http://dx.doi.org/10.3390/cancers15194731.
Full textCarrara, Matteo, Marco Beccuti, Fulvio Lazzarato, Federica Cavallo, Francesca Cordero, Susanna Donatelli, and Raffaele A. Calogero. "State-of-the-Art Fusion-Finder Algorithms Sensitivity and Specificity." BioMed Research International 2013 (2013): 1–6. http://dx.doi.org/10.1155/2013/340620.
Full textFu Hongyu, 付宏语, 巩岩 Gong Yan, 汪路涵 Wang Luhan, 张艳微 Zhang Yanwei, 郎松 Lang Song, 张志 Zhang Zhi, and 郑汉青 Zheng Hanqing. "多聚焦显微图像融合算法." Laser & Optoelectronics Progress 61, no. 6 (2024): 0618022. http://dx.doi.org/10.3788/lop232015.
Full textTan, Yuxiang, Yann Tambouret, and Stefano Monti. "SimFuse: A Novel Fusion Simulator for RNA Sequencing (RNA-Seq) Data." BioMed Research International 2015 (2015): 1–5. http://dx.doi.org/10.1155/2015/780519.
Full textDehghannasiri, Roozbeh, Donald E. Freeman, Milos Jordanski, Gillian L. Hsieh, Ana Damljanovic, Erik Lehnert, and Julia Salzman. "Improved detection of gene fusions by applying statistical methods reveals oncogenic RNA cancer drivers." Proceedings of the National Academy of Sciences 116, no. 31 (July 15, 2019): 15524–33. http://dx.doi.org/10.1073/pnas.1900391116.
Full textNandeesh, M. D., and Dr M. Meenakshi. "Image Fusion Algorithms for Medical Images-A Comparison." Bonfring International Journal of Advances in Image Processing 5, no. 3 (July 31, 2015): 23–26. http://dx.doi.org/10.9756/bijaip.8051.
Full textKaran, Canan, Elaine Tan, Humaira Sarfraz, Christine Marie Walko, Richard D. Kim, Todd C. Knepper, and Ibrahim Halil Sahin. "Clinical and molecular characterization of fusion genes in colorectal cancer." Journal of Clinical Oncology 40, no. 16_suppl (June 1, 2022): e15568-e15568. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.e15568.
Full textFoltz, Steven M., Qingsong Gao, Christopher J. Yoon, Amila Weerasinghe, Hua Sun, Lijun Yao, Mark A. Fiala, et al. "Comprehensive Multi-Omics Analysis of Gene Fusions in a Large Multiple Myeloma Cohort." Blood 132, Supplement 1 (November 29, 2018): 1898. http://dx.doi.org/10.1182/blood-2018-99-117245.
Full textThomas, Brad B., Yanglong Mou, Lauryn Keeler, Christophe Magnan, Vincent Funari, Lawrence Weiss, Shari Brown, and Sally Agersborg. "A Highly Sensitive and Specific Gene Fusion Algorithm Based on Multiple Fusion Callers and an Ensemble Machine Learning Approach." Blood 136, Supplement 1 (November 5, 2020): 12–13. http://dx.doi.org/10.1182/blood-2020-142020.
Full textSun, Changqi, Cong Zhang, and Naixue Xiong. "Infrared and Visible Image Fusion Techniques Based on Deep Learning: A Review." Electronics 9, no. 12 (December 17, 2020): 2162. http://dx.doi.org/10.3390/electronics9122162.
Full textDissertations / Theses on the topic "Algorithmes de fusion"
Kaci, Souhila. "Connaissances et préférences : représentation et fusion en logique possibiliste." Toulouse 3, 2002. http://www.theses.fr/2002TOU30029.
Full textZarrouati-Vissière, Nadège. "La réalité augmentée : fusion de vision et navigation." Phd thesis, Ecole Nationale Supérieure des Mines de Paris, 2013. http://pastel.archives-ouvertes.fr/pastel-00961962.
Full textArezki, Yassir. "Algorithmes de références 'robustes' pour la métrologie dimensionnelle des surfaces asphériques et des surfaces complexes en optique." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLN058.
Full textAspheres and freeform surfaces are a very challenging class of optical elements. Their application has grown considerably in the last few years in imaging systems, astronomy, lithography, etc. The metrology for aspheres is very challenging, because of the high dynamic range of the acquired information and the traceability to the SI unit meter. Metrology should make use of the infinite norm; (Minimum Zone Method or Min-Max method) to calculate the envelope enclosing the points in the dataset by minimizing the difference between the maximum deviation and the minimum deviation between the surface and the dataset. This method grows in complexity as the number of points in the dataset increases, and the involved algorithms are non-deterministic. Despite the fact that this method works for simple geometries (lines, planes, circles, cylinders, cones and spheres) it is still a major challenge when used on complex geometries (asphere and freeform surfaces). Therefore, the main objective is to address this key challenge about the development of Min-Max fitting algorithms for both aspherical and freeform surfaces as well as least squares fitting algorithms, in order to provide robust reference algorithms for the large community involved in this domain. The reference algorithms to be developed should be evaluated and validated on several reference data (softgauges) that will be generated using reference data generators
Laporterie, Florence. "Représentations hiérarchiques d'images avec des pyramides morphologiques : application à l'analyse et à la fusion spatio-temporelle de données en observation de la Terre." Toulouse, ENSAE, 2002. http://www.theses.fr/2002ESAE0001.
Full textPoinsot, Audrey. "Traitements pour la reconnaissance biométrique multimodale : algorithmes et architectures." Thesis, Dijon, 2011. http://www.theses.fr/2011DIJOS010.
Full textIncluding multiple sources of information in personal identity recognition reduces the limitations of each used characteristic and gives the opportunity to greatly improve performance. This thesis presents the design work done in order to build an efficient generalpublic recognition system, which can be implemented on a low-cost hardware platform. The chosen solution explores the possibilities offered by multimodality and in particular by the fusion of face and palmprint. The algorithmic chain consists in a processing based on Gabor filters and score fusion. A real database of 130 subjects has been designed and built for the study. High performance has been obtained and confirmed on a virtual database, which consists of two common public biometric databases (AR and PolyU). Thanks to a comprehensive study on the architecture of the DSP components and some implementations carried out on a DSP belonging to the TMS320c64x family, it has been proved that it is possible to implement the system on a single DSP with short processing times. Moreover, an algorithms and architectures development work for FPGA implementation has demonstrated that these times can be significantly reduced
Awad, Mohamad M. "Mise en oeuvre d'un système coopératif adaptatif de segmentation d'images multicomposantes." Rennes 1, 2008. http://www.theses.fr/2008REN1S031.
Full textDans le domaine de la télédétection, l'exploitation des images acquises par divers capteurs présente un large champ d'investigation et pose de nombreux problèmes à tous les niveaux dans la chaîne de traitement des images. Aussi, le développement d’approches de segmentation et de fusion optimisées et adaptatives, s’avère indispensable. La segmentation et la fusion sont deux étapes essentielles dans tout système de reconnaissance ou d’interprétation par vision: Le taux d'identification ou la qualité de l'interprétation dépend en effet, étroitement de la qualité de l'analyse et la pertinence des résultats de ces phases. Bien que le sujet ait été étudié en détail dans la littérature, il n'existe pas de méthodes universelles et efficaces de segmentation et de fusion qui permettent une identification précise des classes d'une image réelle lorsque celle-ci est composée à la fois de régions uniformes (faible variation locale de luminance) et texturées. En outre, la majorité de ces méthodes nécessitent des connaissances a priori qui sont en pratique difficilement accessibles. En outre, certaines d’entre elles supposent l'existence de modèles dont les paramètres doivent être estimés. Toutefois, une telle approche paramétrique est non robuste et ses performances sont sévèrement altérées par l’ajustement de l'utilisation de modèles paramétriques. Dans le cadre de cette thèse, un système coopératif et adaptatif de segmentation des images multicomposantes est développé. Ce système est non-paramétrique et utilise le minimum de connaissances a priori. Il permet l’analyse de l'image à plusieurs niveaux hiérarchiques en fonction de la complexité tout en intégrant plusieurs méthodes dans les mécanismes de coopération. Trois approches sont intégrées dans le processus coopératif: L’Algorithme Génétique Hybride, l'Algorithme des C-Moyennes Floues, le Réseau de Kohonen (SOM) et la modélisation géométrique par ’’Non-Uniform Rational B-Spline’’. Pour fusionner les différents résultats issus des méthodes coopératives, l’algorithme génétique est appliqué. Le système est évalué sur des images multicomposantes satellitaires et aériennes. Les différents résultats obtenus montrent la grande efficacité et la précision de ce système
Khiari, Nefissa. "Biométrie multimodale basée sur l’iris et le visage." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLE014/document.
Full textThis thesis aims to make a contribution in the field of biometrics based on iris (one of the most accurate and hard to hack biometrics) in conjunction with face (one of the cheapest and less intrusive biometrics).Through this work, we discuss several important aspects of unimodal and multimodal biometrics. After an overview on unimodal and multimodal biometrics based on iris and face, we propose several personal approaches of biometric authentication using each single trait. Particularly, we address facial recognition first with conventional approaches based on combined algorithms, then with bio-inspired approaches emulating the human vision mechanism. We demonstrate the interest of bio-inspired approaches over conventional approaches through two proposed methods. The first one exploits the results of neuroscientific work indicating the relevant regions and scales in a face identification task. The second consists in applying a rank order coding method at the preprocessing step so as to enhance the information content of face images.We keep the best unimodal approach of iris and face recognition to design two multimodal biometric methods. Through these methods, we evaluate different classic strategies of multimodal score-level fusion. Afterwards, we propose a new score-level fusion rule based on a quality metric according to irises occultation rates. Then, we point out the interest of the double-sample iris aspect in a multimodal approach.All the proposed methods are evaluated on the real multimodal IV² database captured under variable to degraded environments, and following a specific protocol provided as part of the IV² evaluation campaign. After a comparative study with the participant algorithms in the IV² campaign, we prove the competitiveness of our algorithms witch outperform most of the participant ones in the IV² campaign in many experiments
Salmeron-Quiroz, Bernardino Benito. "Fusion de données multicapteurs pour la capture de mouvement." Phd thesis, Université Joseph Fourier (Grenoble), 2007. http://tel.archives-ouvertes.fr/tel-00148577.
Full textSalmeron-Quiroz, Bernardino Benito. "Fusion de données multicapteurs pour la capture de mouvement." Phd thesis, Grenoble 1, 2007. http://www.theses.fr/2007GRE10062.
Full textThis thesis deals with motion capture (MoCap) which goal is to acquire the attitude of human's body. In our case, the arm and the leg are considered. The MoCap trackers are made of "software" and "hardware" parts which allow acquisition of the movement of an object or a human in space in real or differed time. Many MoCaps systems still exist, but they require an adaptation of the environment. In this thesis, a low cost, low weight attitude central unit (UCN namely a triaxes magnetometer and a triaxes accelerometer), is used. This attitude central unit has been developed within the CEA-LETI. In this work, we propose different algorithms to estimate the attitude and the linear accelerations of a rigid body. For the rotation parametrization, the unit quaternion is used. Firstly, the estimation of the attitude and the accelerations (6DDL case) from the measurements provided by ACU is done via an optimization technique. The motion capture of articulated chains (arm and leg) is also studied with ad-hoc assumptions on the accelerations in the pivot connections, the orientation of the segments as well as the accelerations in particular points of the segments can be estimated. The different approaches proposed in this work have been evaluated with simulated data and real data
Bader, Kaci. "Tolérance aux fautes pour la perception multi-capteurs : application à la localisation d'un véhicule intelligent." Thesis, Compiègne, 2014. http://www.theses.fr/2014COMP2161/document.
Full textPerception is a fundamental input for robotic systems, particularly for positioning, navigation and interaction with the environment. But the data perceived by these systems are often complex and subject to significant imprecision. To overcome these problems, the multi-sensor approach uses either multiple sensors of the same type to exploit their redundancy or sensors of different types for exploiting their complementarity to reduce the sensors inaccuracies and uncertainties. The validation of the data fusion approach raises two major problems. First, the behavior of fusion algorithms is difficult to predict, which makes them difficult to verify by formal approaches. In addition, the open environment of robotic systems generates a very large execution context, which makes the tests difficult and costly. The purpose of this work is to propose an alternative to validation by developing fault tolerance mechanisms : since it is difficult to eliminate all the errors of the perceptual system, We will try to limit impact in their operation. We studied the inherently fault tolerance allowed by data fusion by formally analyzing the data fusion algorithms, and we have proposed detection and recovery mechanisms suitable for multi-sensor perception, we implemented the proposed mechanisms on vehicle localization application using Kalman filltering data fusion. We evaluated the proposed mechanims using the real data replay and fault injection technique
Books on the topic "Algorithmes de fusion"
service), ScienceDirect (Online, ed. Image fusion: Algorithms and applications. Amsterdam: Academic Press/Elsevier, 2008.
Find full textAntony, Richard T. Principles of data fusion automation. Boston: Artech House, 1995.
Find full textAbdelgawad, Ahmed, and Magdy Bayoumi. Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-1350-9.
Full textAbdelgawad, Ahmed. Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks. Boston, MA: Springer US, 2012.
Find full textC, Jain L., and Martin N. M, eds. Fusion of neural networks, fuzzy sets, and genetic algorithms: Industrial applications. Boca Raton: CRC press, 1999.
Find full textCarpenter, J. Russell. Progress in navigation filter estimate fusion and its application to spacecraft rendezvous. [Washington, D.C.]: National Aeronautics and Space Administration, 1994.
Find full textCarpenter, J. Russell. Progress in navigation filter estimate fusion and its application to spacecraft rendezvous. [Washington, D.C.]: National Aeronautics and Space Administration, 1994.
Find full textV, Dasarathy Belur, and Society of Photo-optical Instrumentation Engineers., eds. Sensor fusion--architectures, algorithms, and applications III: 7-9 April 1999, Orlando, Florida. Bellingham, Wash: SPIE, 1999.
Find full textV, Dasarathy Belur, and Society of Photo-optical Instrumentation Engineers., eds. Sensor fusion--architectures, algorithms, and applications II: 16-17 April 1998, Orlando, Florida. Bellingham, Wash: SPIE, 1998.
Find full textV, Dasarathy Belur, and Society of Photo-optical Instrumentation Engineers., eds. Sensor fusion--architectures, algorithms, and applications V: 18-20 April, 2001, Orlando, USA. Bellingham, Wash: SPIE, 2001.
Find full textBook chapters on the topic "Algorithmes de fusion"
Jøsang, Audun. "Belief Fusion." In Artificial Intelligence: Foundations, Theory, and Algorithms, 207–36. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-42337-1_12.
Full textNimier, V. "Soft Sensor Management for Multisensor Tracking Algorithm." In Multisensor Fusion, 365–79. Dordrecht: Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-010-0556-2_15.
Full textWang, Dayi, Maodeng Li, Xiangyu Huang, and Xiaowen Zhang. "Estimation Fusion Algorithm." In Space Science and Technologies, 63–89. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4879-6_3.
Full textNehiwal, Jayesh, Harish Kumar Khyani, Shrawan Ram Patel, and Chandershekhar Singh. "Nuclear Fusion: Energy of Future." In Algorithms for Intelligent Systems, 295–301. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8820-4_28.
Full textJouan, A., B. Jarry, and H. Michalska. "Tracking Closely Maneuvering Targets in Clutter with an IMM-JVC Algorithm." In Multisensor Fusion, 581–92. Dordrecht: Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-010-0556-2_27.
Full textTurhan-Sayan, G. "Multi-Aspect Data Fusion Applied to Electromagnetic Target Classification using Enetic Algorithm." In Multisensor Fusion, 533–39. Dordrecht: Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-010-0556-2_24.
Full textAbdelgawad, Ahmed, and Magdy Bayoumi. "Proposed Centralized Data Fusion Algorithms." In Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks, 37–57. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-1350-9_3.
Full textOnoue, Y., Z. Hu, H. Iwasaki, and M. Takeichi. "A Calculational Fusion System HYLO." In Algorithmic Languages and Calculi, 76–106. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-0-387-35264-0_4.
Full textvan Inge, Anthony, L. O. Hertzberger, A. G. Starreveld, and F. C. A. Groen. "Algorithms on a SIMD processor array." In Multisensor Fusion for Computer Vision, 307–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-662-02957-2_18.
Full textFosbury, Adam M., John L. Crassidis, and Jemin George. "Contextual Tracking in Surface Applications: Algorithms and Design Examples." In Context-Enhanced Information Fusion, 339–79. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28971-7_13.
Full textConference papers on the topic "Algorithmes de fusion"
Ismail, Hesham, and Balakumar Balachandran. "Feature Extraction Algorithm Fusion for SONAR Sensor Data Based Environment Mapping." In ASME 2014 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/imece2014-37116.
Full textAbdolsamadi, Amirmahyar, Pingfeng Wang, and Prasanna Tamilselvan. "A Generic Fusion Platform of Failure Diagnostics for Resilient Engineering System Design." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47009.
Full textYousif, Ahmed Luay Yousif, and Mohamed Elsobky. "LIDAR Phenomenological Sensor Model: Development and Validation." In Mobility 4.0. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2023. http://dx.doi.org/10.4271/2023-01-1902.
Full textTamilselvan, Prasanna, Pingfeng Wang, and Chao Hu. "Design of a Robust Classification Fusion Platform for Structural Health Diagnostics." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12601.
Full textRoussel, Stephane, Hemanth Porumamilla, Charles Birdsong, Peter Schuster, and Christopher Clark. "Enhanced Vehicle Identification Utilizing Sensor Fusion and Statistical Algorithms." In ASME 2009 International Mechanical Engineering Congress and Exposition. ASMEDC, 2009. http://dx.doi.org/10.1115/imece2009-12012.
Full textWen, Yao-Jung, Alice M. Agogino, and Kai Goebel. "Fuzzy Validation and Fusion for Wireless Sensor Networks." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-60964.
Full textMunro, Deborah S., and Munish C. Gupta. "Correlation of Strain on Instrumentation to Simulated Posterolateral Lumbar Fusion in a Sheep Model." In ASME 2016 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/imece2016-65696.
Full textSkonnikov, Petr Nikolaevich. "Comparative Analysis of Image Fusion Techniques." In 32nd International Conference on Computer Graphics and Vision. Keldysh Institute of Applied Mathematics, 2022. http://dx.doi.org/10.20948/graphicon-2022-449-454.
Full textBather, J. "Tracking and data fusion." In IEE International Seminar Target Tracking: Algorithms and Applications. IEE, 2001. http://dx.doi.org/10.1049/ic:20010234.
Full textMa, Liyao, Bin Sun, and Chunyan Han. "Training Instance Random Sampling Based Evidential Classification Forest Algorithms." In 2018 International Conference on Information Fusion (FUSION). IEEE, 2018. http://dx.doi.org/10.23919/icif.2018.8455427.
Full textReports on the topic "Algorithmes de fusion"
Meyer, David, and Jeffrey Remmel. Distributed Algorithms for Sensor Fusion. Fort Belvoir, VA: Defense Technical Information Center, October 2002. http://dx.doi.org/10.21236/ada415039.
Full textYocky, D. A., M. D. Chadwick, S. P. Goudy, and D. K. Johnson. Multisensor data fusion algorithm development. Office of Scientific and Technical Information (OSTI), December 1995. http://dx.doi.org/10.2172/172138.
Full textPao, Lucy Y. Distributed Multisensor Fusion Algorithms for Tracking Applications. Fort Belvoir, VA: Defense Technical Information Center, May 2000. http://dx.doi.org/10.21236/ada377900.
Full textBassu, Devasis. Fast Multiscale Algorithms for Information Representation and Fusion. Fort Belvoir, VA: Defense Technical Information Center, April 2013. http://dx.doi.org/10.21236/ada608426.
Full textBassu, Devasis. Fast Multiscale Algorithms for Information Representation and Fusion. Fort Belvoir, VA: Defense Technical Information Center, January 2011. http://dx.doi.org/10.21236/ada538312.
Full textVarshney, Pramod K., Chilukuri K. Mohan, and Krishan G. Mehrotra. Adaptive Models and Fusion Algorithms for Information Exploitation. Fort Belvoir, VA: Defense Technical Information Center, May 2009. http://dx.doi.org/10.21236/ada516533.
Full textBassu, Devasis. Fast Multiscale Algorithms for Information Representation and Fusion. Fort Belvoir, VA: Defense Technical Information Center, July 2012. http://dx.doi.org/10.21236/ada565467.
Full textBassu, Devasis. Fast Multiscale Algorithms for Information Representation and Fusion. Fort Belvoir, VA: Defense Technical Information Center, October 2012. http://dx.doi.org/10.21236/ada570238.
Full textBassu, Devasis. Fast Multiscale Algorithms for Information Representation and Fusion. Fort Belvoir, VA: Defense Technical Information Center, January 2013. http://dx.doi.org/10.21236/ada574842.
Full textDVore, Ronald A. New Theory and Algorithms for Scalable Data Fusion. Fort Belvoir, VA: Defense Technical Information Center, June 2013. http://dx.doi.org/10.21236/ada587535.
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