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Artykuły w czasopismach na temat "Object characterization"
Grekov, R., i A. Borisov. "CHARACTERIZATION OF THE EFFICIENCY OF THE FEATURES AGGREGATE IN FUZZY PATTERN RECOGNITION TASK". Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 1 (27.06.1997): 78. http://dx.doi.org/10.17770/etr1997vol1.1858.
Pełny tekst źródłaPeli, T. "Multiscale fractal theory and object characterization". Journal of the Optical Society of America A 7, nr 6 (1.06.1990): 1101. http://dx.doi.org/10.1364/josaa.7.001101.
Pełny tekst źródłaAijazi, A. K., L. Malaterre, L. Trassoudaine i P. Checchin. "SYSTEMATIC EVALUATION AND CHARACTERIZATION OF 3D SOLID STATE LIDAR SENSORS FOR AUTONOMOUS GROUND VEHICLES". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B1-2020 (6.08.2020): 199–203. http://dx.doi.org/10.5194/isprs-archives-xliii-b1-2020-199-2020.
Pełny tekst źródłaMALGOUYRES, RÉMY, i GILLES BERTRAND. "COMPLETE LOCAL CHARACTERIZATION OF STRONG 26-SURFACES: CONTINUOUS ANALOGS FOR STRONG 26-SURFACES". International Journal of Pattern Recognition and Artificial Intelligence 13, nr 04 (czerwiec 1999): 465–84. http://dx.doi.org/10.1142/s0218001499000288.
Pełny tekst źródłaHofmann, Martin, i Benjamin Pierce. "A unifying type-theoretic framework for objects". Journal of Functional Programming 5, nr 4 (październik 1995): 593–635. http://dx.doi.org/10.1017/s0956796800001490.
Pełny tekst źródłaRind, F. C. "Intracellular characterization of neurons in the locust brain signaling impending collision". Journal of Neurophysiology 75, nr 3 (1.03.1996): 986–95. http://dx.doi.org/10.1152/jn.1996.75.3.986.
Pełny tekst źródłaSalman, Rahmi, Thorsten Schultze i Ingolf Willms. "Performance Enhancement of UWB Material Characterization and Object Recognition for Security Robots". Journal of Electrical and Computer Engineering 2010 (2010): 1–6. http://dx.doi.org/10.1155/2010/314695.
Pełny tekst źródłaHitchens, Nathan M., Michael E. Baldwin i Robert J. Trapp. "An Object-Oriented Characterization of Extreme Precipitation-Producing Convective Systems in the Midwestern United States". Monthly Weather Review 140, nr 4 (kwiecień 2012): 1356–66. http://dx.doi.org/10.1175/mwr-d-11-00153.1.
Pełny tekst źródłaGuan, Hongliang, Chengyuan Qian, Tingsong Wu, Xiaoming Hu, Fuzhou Duan i Xinyi Ye. "A Dynamic Scene Vision SLAM Method Incorporating Object Detection and Object Characterization". Sustainability 15, nr 4 (8.02.2023): 3048. http://dx.doi.org/10.3390/su15043048.
Pełny tekst źródłaGuo, Xinhua, Yosuke Mizuno i Kentaro Nakamura. "Object Characterization Based on Multispectral Acoustic Imaging". Japanese Journal of Applied Physics 52, nr 12R (1.12.2013): 127301. http://dx.doi.org/10.7567/jjap.52.127301.
Pełny tekst źródłaRozprawy doktorskie na temat "Object characterization"
LaPointe, Jamie. "Adaptive estimation techniques for resident space object characterization". Thesis, The University of Arizona, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10250698.
Pełny tekst źródłaThis thesis investigates using adaptive estimation techniques to determine unknown model parameters such as size and surface material reflectivity, while estimating position, velocity, attitude, and attitude rates of a resident space object. This work focuses on the application of these methods to the space situational awareness problem.
This thesis proposes a unique method of implementing a top-level gating network in a dual-layer hierarchical mixture of experts. In addition it proposes a decaying learning parameter for use in both the single layer mixture of experts and the dual-layer hierarchical mixture of experts. Both a single layer mixture of experts and dual-layer hierarchical mixture of experts are compared to the multiple model adaptive estimation in estimating resident space object parameters such as size and reflectivity. The hierarchical mixture of experts consists of macromodes. Each macromode can estimate a different parameter in parallel. Each macromode is a single layer mixture of experts with unscented Kalman filters used as the experts. A gating network in each macromode determines a gating weight which is used as a hypothesis tester. Then the output of the macromode gating weights go to a top level gating weight to determine which macromode contains the most probable model. The measurements consist of astrometric and photometric data from non-resolved observations of the target gathered via a telescope with a charge coupled device camera. Each filter receives the same measurement sequence. The apparent magnitude measurement model consists of the Ashikhmin Shirley bidirectional reflectance distribution function. The measurements, process models, and the additional shape, mass, and inertia characteristics allow the algorithm to predict the state and select the most probable fit to the size and reflectance characteristics based on the statistics of the measurement residuals and innovation covariance. A simulation code is developed to test these adaptive estimation techniques. The feasibility of these methods will be demonstrated in this thesis.
LaPointe, Jamie J., i Jamie J. LaPointe. "Adaptive Estimation Techniques for Resident Space Object Characterization". Thesis, The University of Arizona, 2016. http://hdl.handle.net/10150/623263.
Pełny tekst źródłaMandadi, Bharath Kumar Reddy. "Advanced Object Characterization and Monitoring Techniques Using Polarimetric Imaging". University of Akron / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=akron1243780947.
Pełny tekst źródłaBiller, Beth A., Johanna Vos, Esther Buenzli, Katelyn Allers, Mickaël Bonnefoy, Benjamin Charnay, Bruno Bézard i in. "Simultaneous Multiwavelength Variability Characterization of the Free-floating Planetary-mass Object PSO J318.5−22". IOP PUBLISHING LTD, 2018. http://hdl.handle.net/10150/627034.
Pełny tekst źródłaFlasseur, Olivier. "Object detection and characterization from faint signals in images : applications in astronomy and microscopy". Thesis, Lyon, 2019. http://www.theses.fr/2019LYSES042.
Pełny tekst źródłaDetecting and characterizing objects in images in the low signal-to-noise ratio regime is a critical issue in many areas such as astronomy or microscopy. In astronomy, the detection of exoplanets and their characterization by direct imaging from the Earth is a hot topic. A target star and its close environment (hosting potential exoplanets) are observed on short exposures. In microscopy, in-line holography is a cost-effective method for characterizing microscopic objects. Based on the recording of a hologram, it allows a digital focusing in any plane of the imaged 3-D volume. In these two fields, the object detection problem is made difficult by the low contrast between the objects and the nonstationary background of the recorded images.In this thesis, we propose an unsupervised exoplanet detection and characterization algorithm based on the statistical modeling of background fluctuations. The method, based on a modeling of the statistical distribution of patches, captures their spatial covariances. It reaches a performance superior to state-of-the-art techniques on several datasets of the European high-contrast imager SPHERE operating at the Very Large Telescope. It produces statistically grounded and spatially-stationary detection maps in which detections can be performed at a constant probability of false alarm. It also produces photometrically unbiased spectral energy distributions of the detected sources. The use of a statistical model of the data leads to reliable photometric and astrometric accuracies. This methodological framework can be adapted to the detection of spatially-extended patterns in strong structured background, such as the diffraction patterns in holographic microscopy. We also propose robust approaches based on weighting strategies to reduce the influence of the numerous outliers present in real data. We show on holographic videos that the proposed weighting approach achieves a bias/variance tradeoff. In astronomy, the robustness improves the performance of our detection method in particular at close separations where the stellar residuals dominate. Our algorithms are adapted to benefit from the possible spectral diversity of the data, which improves the detection and characterization performance. All the algorithms developed are unsupervised: weighting and/or regularization parameters are estimated in a data-driven fashion. Beyond the applications in astronomy and microscopy, the signal processing methodologies introduced are general and could be applied to other detection and estimation problems
Lopes, Alex Cerqueira. "Máscaras: transformações em “Doroteia” de Nelson Rodrigues". Escola de Teatro, 2014. http://repositorio.ufba.br/ri/handle/ri/27042.
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RESUMO Este trabalho trata máscara-objeto e máscara-maquiagem como meiode transformação dos atores no espetáculo “Doroteia”, de Nelson Rodrigues. A dissertação é constituída a partir de experiências com máscaras, tanto objeto quanto maquiagem, apresentando no percurso das vivências a solidificação e base para a concepção e criação dos elementos cênicos em questão. Essainvestigação tem como objetivo abordar a caracterização visual dos personagens no referido espetáculo, com foco nas máscaras supracitadas, destacando sua importância fundamental para a construção do personagem teatral. Posteriormente, são analisadas as aplicabilidades das referidas máscaras nas cenas do espetáculo. As leituras a partir da percepção do espectador acontecem como consequência da consciência coerente com o todo que o portador estabelece.
ABSTRACT This thesis deals with mask-object and mask-make up asinstruments of transformation of the actors at Nelson Rodrigues’ play, “Doroteia”. The dissertation is built over experiences with mask-object and mask-make up, introducing during the process the solidification and basis for conception and creation of the scenic elements being studied. This investigation aims to broach the visual characterization of the characters in the play, focusing on the two previously mentioned masks, emphasizing their fundamental importance for the theatrical character’s construction. Subsequently, the applicability of the masks will be analyzed in the scenes of the play. The readings from the spectator’s perception happen as consequence of the conscience consistent with the whole established by the mask’s wearer.
Al, Hayek Marianne. "Modélisation optique de signatures spectrales et polarimétriques d'objets pour augmenter les performances d'un système de reconnaissance". Electronic Thesis or Diss., Brest, 2023. http://www.theses.fr/2023BRES0101.
Pełny tekst źródłaConventional imaging, limited to object shapes and colors, faces limitations in object recognition. To enhance imaging system performance, hyperspectral and polarimetric imaging provides a wealth of information, includingchallenging-to-obtain physical parameters. This facilitates improved object detection, quantitative characterization, and classification. However, the processing of complex data from these modalities remains a challenge. The aim of this work is to propose a generic methodology for the analysis of optical signals, with a primary focus on hyperspectral imaging (HSI). An original classification of invertible physics-based hyperspectral models is presented, along with descriptions of recent diverse models for various applications: MPBOM for algae and bacteria biofilm, MARMIT for soil, PROSPECT for plant leaves, Farrell for turbid biological tissues, Schmitt for human skin, and Hapke for objects in the solar system. A convergence between the PROSPECT and Farrell models for intermediate objects (green apple and leek) paves the way for the development of a new generic and comprehensive modeling approach.Particularly in the field of biology, in collaboration with the ANSES laboratory, we conducted early detection ollowed by quantification of biofilms forming in fish farming basins using hyperspectral and polarimetric imaging. This is crucial as the current visual detection method is not efficient in preventing biofilm accumulation and implementingcleaning and disinfection procedures. Hence, an initial version of a dedicated physical modeling approach called "DNA-HSI" has been established
Fernandes, Lénia Janete Oliveira. "Characterization and identification of printed objects". Master's thesis, FCT - UNL, 2008. http://hdl.handle.net/10362/1763.
Pełny tekst źródłaGoh, Jinzhong Jeremy [Verfasser], Denise [Gutachter] Manahan-Vaughan i Klaus-Peter [Gutachter] Hoffmann. "Characterization of the effects of novel object-space information on synaptic plasticity in the hippocampal CA1 sub-region of freely behaving mice / Jinzhong Jeremy Goh ; Gutachter: Denise Manahan-Vaughan, Klaus-Peter Hoffmann ; International Graduate School of Neuroscience". Bochum : Ruhr-Universität Bochum, 2013. http://d-nb.info/1212660749/34.
Pełny tekst źródłabin, Ahmad Khairuddin Taufiq. "Characterization of objects by fitting the polarization tensor". Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/characterization-of-objects-by-fitting-the-polarization-tensor(1ee0de67-fdd4-4fae-ba00-3f2e4f3987a8).html.
Pełny tekst źródłaKsiążki na temat "Object characterization"
Scott, Carroll, Zimmt Werner S, Spurgeon David 1962- i Lane Stacey K, red. Material characterization tests for objects of art and archaeology. Wyd. 2. London: Archetype Publications, 2005.
Znajdź pełny tekst źródłaFoliage penetration radar: Detection and characterization of objects under trees. Raleigh, NC: SciTech Pub., 2011.
Znajdź pełny tekst źródłaGril, Joseph, red. Wood Science for Conservation of Cultural Heritage – Braga 2008. Florence: Firenze University Press, 2010. http://dx.doi.org/10.36253/978-88-6453-165-6.
Pełny tekst źródłaRieger, Christopher. Faulkner’s Fashion. Bloomsbury Publishing Inc, 2023. http://dx.doi.org/10.5040/9798765103982.
Pełny tekst źródłaAzzouni, Jody. Ontology Without Borders. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190622558.001.0001.
Pełny tekst źródłaAzzouni, Jody. Feature-Characterization Languages. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190622558.003.0009.
Pełny tekst źródłaPfeiffer, Christian. Body in Categories 6. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198779728.003.0005.
Pełny tekst źródłaOdegaard, Nancy. Material Characterization Tests for Objects of Art. Wyd. 2. Archetype Books, 2005.
Znajdź pełny tekst źródłaBistatic Radar Cross Section (RCS) Characterization of Complex Objects. Storming Media, 1999.
Znajdź pełny tekst źródłaOdegaard, Nancy, Scott Carroll i Werner S. Zimmt. Material Characterization Tests for Objects of Art and Archaeology. Archetype Publications Ltd, 2000.
Znajdź pełny tekst źródłaCzęści książek na temat "Object characterization"
Burghouts, Gertjan J. "Task-Specific Novel Object Characterization". W Pattern Recognition. ICPR International Workshops and Challenges, 447–55. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68799-1_33.
Pełny tekst źródłaSirotti, Paolo. "Optical Joint Fourier Transform Correlation for Phase Object Recognition". W Nondestructive Characterization of Materials II, 753–60. Boston, MA: Springer US, 1987. http://dx.doi.org/10.1007/978-1-4684-5338-6_78.
Pełny tekst źródłaAndersen, Jens Damgaard. "Combinatorial characterization of perspective projections from polyhedral object scenes". W Computer Vision — ECCV 90, 557–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/bfb0014906.
Pełny tekst źródłaBouchaud, François, Thomas Vantroys i Alexandre Boe. "Characterization of a Connected Object by Its Acoustic Signature". W Lecture Notes in Networks and Systems, 19–32. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98015-3_2.
Pełny tekst źródłaLandabaso, José Luis, i Montse Pardàs. "Foreground Regions Extraction and Characterization Towards Real-Time Object Tracking". W Machine Learning for Multimodal Interaction, 241–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11677482_21.
Pełny tekst źródłaVascon, Sebastiano, Ylenia Parin, Eis Annavini, Mattia D’Andola, Davide Zoccolan i Marcello Pelillo. "Characterization of Visual Object Representations in Rat Primary Visual Cortex". W Lecture Notes in Computer Science, 577–86. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-11015-4_43.
Pełny tekst źródłaWu, Shenming, Yishuo Huang, Yu-Min Su i Yuan-Zhih Lin. "Evaluating the Thermal Characteristics of Rubberized Asphalt by Applying the Object-Based Approach". W Testing and Characterization of Asphalt Materials and Pavement Structures, 12–20. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95789-0_2.
Pełny tekst źródłaHabibi, Golnaz, Sándor P. Fekete, Zachary Kingston i James McLurkin. "Distributed Object Characterization with Local Sensing by a Multi-robot System". W Distributed Autonomous Robotic Systems, 205–18. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73008-0_15.
Pełny tekst źródłaOsip, David J., S. D. Kern i J. L. Elliot. "Physical Characterization of the Binary Edgeworth—Kuiper Belt Object 2001 QT297". W The First Decadal Review of the Edgeworth-Kuiper Belt, 409–21. Dordrecht: Springer Netherlands, 2004. http://dx.doi.org/10.1007/978-94-017-3321-2_35.
Pełny tekst źródłaYao, Wei, i Jianwei Wu. "Airborne LiDAR for Detection and Characterization of Urban Objects and Traffic Dynamics". W Urban Informatics, 367–400. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8983-6_22.
Pełny tekst źródłaStreszczenia konferencji na temat "Object characterization"
Jackin, B. J., P. K. Palanisamy, T. Yatagai, P. Predeep, Mrinal Thakur i M. K. Ravi Varma. "Retrieving Full Object Information from Partial Object Information using Digital Holography". W OPTICS: PHENOMENA, MATERIALS, DEVICES, AND CHARACTERIZATION: OPTICS 2011: International Conference on Light. AIP, 2011. http://dx.doi.org/10.1063/1.3643532.
Pełny tekst źródłaLeu, Jia-Guu, Ishwar K. Sethi i Tao Hong. "Object Surface Characterization From Range Images". W SPIE International Symposium on Optical Engineering and Industrial Sensing for Advance Manufacturing Technologies, redaktor Wayne Wiitanen. SPIE, 1988. http://dx.doi.org/10.1117/12.947688.
Pełny tekst źródłaDavoudi, Mahsa Razavi, i Fereidoon Shams Aliee. "Characterization of Enterprise Architecture quality attributes". W 2009 13th Enterprise Distributed Object Computing Conference Workshops, EDOCW. IEEE, 2009. http://dx.doi.org/10.1109/edocw.2009.5332004.
Pełny tekst źródłaAlvarez, Yuri, Fernando Las-Heras, Borja Gonzalez-Valdes, Jose Angel Martinez-Lorenzo i Carey M. Rappaport. "Low permittivity dielectric object on conductor characterization". W 2013 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting. IEEE, 2013. http://dx.doi.org/10.1109/aps.2013.6711070.
Pełny tekst źródłaLuu, K. Kim, Joshua Snodgrass, Charles L. Matson, S. Maile Giffin, Kris Hamada i John V. Lambert. "Space object characterization from spectral nonimaging data". W Frontiers in Optics. Washington, D.C.: OSA, 2003. http://dx.doi.org/10.1364/fio.2003.tuk2.
Pełny tekst źródłaAkhmedzhanov, I. M., D. V. Baranov i Evgeny M. Zolotov. "Object characterization with the differential heterodyne microscope". W 19th Congress of the International Commission for Optics: Optics for the Quality of Life, redaktorzy Giancarlo C. Righini i Anna Consortini. SPIE, 2003. http://dx.doi.org/10.1117/12.530763.
Pełny tekst źródłaFlasseur, Olivier, Loic Denis, Corinne Fournier i Eric Thiebaut. "Robust object characterization from lensless microscopy videos". W 2017 25th European Signal Processing Conference (EUSIPCO). IEEE, 2017. http://dx.doi.org/10.23919/eusipco.2017.8081448.
Pełny tekst źródłaDing, Bao Ming, Yixin Huangfu i Saeid Habibi. "Uncertainty Characterization for 3D Object Detection Algorithms". W 2023 IEEE Transportation Electrification Conference & Expo (ITEC). IEEE, 2023. http://dx.doi.org/10.1109/itec55900.2023.10186985.
Pełny tekst źródłaTseng, Po-Hang, Jin-Tang Lin, Xin-Yu Liao, Sheng-Lin Lee, Mei-Chun Lin, Yen-Lin Huang, Pei-Jen Lou i Chen-Yuan Dong. "Calculating tumor proportional score of HNSCC patients with deep learning object detection". W Emerging Technologies for Cell and Tissue Characterization, redaktorzy Arjen Amelink, Seemantini K. Nadkarni i Giuliano Scarcelli. SPIE, 2021. http://dx.doi.org/10.1117/12.2615639.
Pełny tekst źródłaMaier, Georg, Florian Pfaff, Florian Becker, Christoph Pieper, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden i in. "Improving material characterization in sensor-based sorting by utilizing motion information". W OCM 2017 - 3rd International Conference on Optical Characterization of Materials. KIT Scientific Publishing, 2017. http://dx.doi.org/10.58895/ksp/1000063696-11.
Pełny tekst źródłaRaporty organizacyjne na temat "Object characterization"
Johnson, R. An object-oriented approach to site characterization decision support. Office of Scientific and Technical Information (OSTI), czerwiec 1995. http://dx.doi.org/10.2172/78721.
Pełny tekst źródłaHofmann, Peter, Robert Marschallinger, Michael Unterwurzacher i Fritz Zobl. Designation of marble provenance: State-of-the-art rock fabric characterization in thin sections by object based image analysis. Cogeo@oeaw-giscience, wrzesień 2011. http://dx.doi.org/10.5242/iamg.2011.0284.
Pełny tekst źródłaGritzo, L. A., J. L. Moya i D. Murray. Fire characterization and object thermal response for a large flat plate adjacent to a large JP-4 fuel fire. Office of Scientific and Technical Information (OSTI), styczeń 1997. http://dx.doi.org/10.2172/437679.
Pełny tekst źródłaChinn, D., R. Huber, D. Chambers, G. Cole, O. Balogun, J. Spicer i T. Murray. Acoustic Characterization of Mesoscale Objects. Office of Scientific and Technical Information (OSTI), marzec 2007. http://dx.doi.org/10.2172/969531.
Pełny tekst źródłaHsieh, Chung-kao Peter. Laser-ultrasound characterization of spherical objects. G.L. report No. 5097. Office of Scientific and Technical Information (OSTI), czerwiec 1993. http://dx.doi.org/10.2172/10143768.
Pełny tekst źródłaBulaevskaya, V. Probabilistic Characterization of Partial Volume Effects in Imaging of Rectangular Objects. Office of Scientific and Technical Information (OSTI), maj 2015. http://dx.doi.org/10.2172/1184185.
Pełny tekst źródłaKoegler, Wendy S., i W. Philip, Jr Kegelmeyer. One user's report on Sandia data objects : evaluation of the DOL and PMO for use in feature characterization. Office of Scientific and Technical Information (OSTI), listopad 2003. http://dx.doi.org/10.2172/918321.
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