Bibliografías temáticas / Classification

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Literatura académica sobre el tema "Classification"

Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 25 de julio de 2025

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Artículos de revistas sobre el tema "Classification"

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Thomas, Pravin, Anand Kumar, Ahamed Subir, et al. "Classification of Head, Neck, and Face Pains First Edition (WHS-MCH1): Position paper of the WHS Classification Committee." Headache Medicine Connections 1, no. 1 (2021): 1–108. http://dx.doi.org/10.52828/hmc.v1i1.classifications.

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Willatt, D. J., M. S. McCormick, R. P. Morton, and P. M. Stell. "Staging of Maxillary Cancer." Annals of Otology, Rhinology & Laryngology 96, no. 2 (1987): 137–41. http://dx.doi.org/10.1177/000348948709600201.

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Of the many proposed classifications for staging maxillary sinus cancer, none has been adopted universally and none is known to be superior to the others. This study identified the best of six currently used classifications using data from 53 previously untreated patients with squamous cell carcinoma of the maxillary sinus. Analysis of each classification's ability to stage the majority of patients, produce a balanced distribution of T stages, and correlate T stage with treatment and prognosis revealed Harrison's classification to be the best. Harrison's classification should be adopted worldw
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Jacob, Elin K. "Proposal for a Classification of Classifications built on Beghtol’s Distinction between “Naïve Classification” and “Professional Classification”." KNOWLEDGE ORGANIZATION 37, no. 2 (2010): 111–20. http://dx.doi.org/10.5771/0943-7444-2010-2-111.

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Feleke, Tekabe Legesse. "Ethiosemitic languages: Classifications and classification determinants." Ampersand 8 (2021): 100074. http://dx.doi.org/10.1016/j.amper.2021.100074.

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Dozic, Slobodan, Dubravka Cvetkovic-Dozic, Milica Skender-Gazibara, and Branko Dozic. "Review of the World Health Organization classification of tumors of the nervous system." Archive of Oncology 10, no. 3 (2002): 175–77. http://dx.doi.org/10.2298/aoo0203175d.

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(Conclusion) Classifications of the nervous system tumors should be neither static nor definitive. The most recent, third, current WHO classification of nervous system tumors was published in 2000. Many substantial changes were introduced. New entities include the chordoid glioma of the third ventricle, the atypical teratoid/rhabdoid tumor, cerebellar liponeurocytoma (the former lipomatous medulloblstoma of the cerebellum), solitary fibrous tumor and perineurioma. The new tumor variants include the large cell medulloblastoma, tanacytic ependymoma and rhabdoid meningioma. Several essential chan
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Fedorova, Natalia. "BASIC CLASSIFIERS OF FORMAL CLASSIFICATION THEORY OF TECHNICAL SYSTEMS: HIERARCHIES, VECTORS AND MATRICES, BANDS." Vestnik of Astrakhan State Technical University. Series: Management, computer science and informatics 2021, no. 3 (2021): 28–40. http://dx.doi.org/10.24143/2072-9502-2021-3-28-40.

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The article considers the importance of a technical system among other technical systems in order to ensure its functioning and development, to classify objects, subjects, processes of the technical and related systems. Previously, the author presented the basics of the formal classification theory. This article describes the basic classifiers and operations with them. Three types of basic classifications are identified: discrete hierarchical, discrete matrix and continuous band classifications. For them the concept, structure, dimension, basic operations (addition, multiplication, equality) a
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Vu, Catphuong, and David Gendelberg. "Classifications in Brief: AO Thoracolumbar Classification System." Clinical Orthopaedics & Related Research 478, no. 2 (2019): 434–40. http://dx.doi.org/10.1097/corr.0000000000001086.

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Di Lauro, Salvatore, Mustafa R. Kadhim, David G. Charteris, and J. Carlos Pastor. "Classifications for Proliferative Vitreoretinopathy (PVR): An Analysis of Their Use in Publications over the Last 15 Years." Journal of Ophthalmology 2016 (2016): 1–6. http://dx.doi.org/10.1155/2016/7807596.

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Purpose. To evaluate the current and suitable use of current proliferative vitreoretinopathy (PVR) classifications in clinical publications related to treatment.Methods. A PubMed search was undertaken using the term “proliferative vitreoretinopathy therapy”. Outcome parameters were the reported PVR classification and PVR grades. The way the classifications were used in comparison to the original description was analyzed. Classification errors were also included. It was also noted whether classifications were used for comparison before and after pharmacological or surgical treatment.Results. 13
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Kozhanov, Anton L., and Oleg V. Voevodin. "ON RECLAMATION PUMPING STATIONS CLASSIFICATION." Land Reclamation and Hydraulic Engineering 14, no. 3 (2024): 261–83. http://dx.doi.org/10.31774/2712-9357-2024-14-3-261-283.

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Purpose: analysis and construction of hierarchical and facet classifications of reclamation pumping stations (RPS). During the research, a search, analysis, comparison and systematization of RPS types were carried out in accordance with regulatory and technical documentation, as well as the developments of various Russian scientists. When developing and constructing RPS classifications, the following methods were used: facet and hierarchical. Discussion. As a result of the study and analysis of various sources of information, it was found that the existing RPS classifications in most cases are
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Fortune, Nicola, Stephanie Short, and Richard Madden. "Building a statistical classification: A new tool for classification development and testing." Statistical Journal of the IAOS 36, no. 4 (2020): 1213–21. http://dx.doi.org/10.3233/sji-200633.

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Statistical classifications are essential for collecting consistent data that can be compared over space and time. However, a publicly-documented body of practice concerning how to undertake the development and testing of a statistical classification is currently lacking. What aspects of the classification should be tested during the development process? How do we judge whether the classification is fit-for-purpose? How should problems and shortcomings be identified so that they can be remedied? To fill this gap, we drew on existing, authoritative sources to develop an analytic structure for u
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Tesis sobre el tema "Classification"

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Bogers, Toine, Willem Thoonen, and den Bosch Antal van. "Expertise classification: Collaborative classification vs. automatic extraction." dLIST, 2006. http://hdl.handle.net/10150/105709.

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Social classification is the process in which a community of users categorizes the resources in that community for their own use. Given enough users and categorization, this will lead to any given resource being represented by a set of labels or descriptors shared throughout the community (Mathes, 2004). Social classification has become an extremely popular way of structuring online communities in recent years. Well-known examples of such communities are the bookmarking websites Furl (http://www.furl.net/) and del.icio.us (http://del.icio.us/), and Flickr (http://www.flickr.com/) where users c
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Ravindra, Dilip. "Firmware and classification algorithm development for vehicle classification." Thesis, California State University, Long Beach, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1603749.

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<p> Vehicle classification is one of the active research topic in Intelligent Transport System. This project proposes an approach to classify the vehicles on freeway with respect to the size of the vehicle. This vehicle classification is based on threshold based algorithm. This system consists of two AMR magneto-resistive sensors connected to TI msp430 development board. The data collected from the two magneto resistive sensors is analyzed and supplied to threshold based algorithm to differentiate the vehicles. With the use of minimum number features extracted from the data it was possible to
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Phillips, Rhonda D. "A Probabilistic Classification Algorithm With Soft Classification Output." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/26701.

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This thesis presents a shared memory parallel version of the hybrid classification algorithm IGSCR (iterative guided spectral class rejection), a novel data reduction technique that can be used in conjunction with PIGSCR (parallel IGSCR), a noise removal method based on the maximum noise fraction (MNF), and a continuous version of IGSCR (CIGSCR) that outputs soft classifications. All of the above are either classification algorithms or preprocessing algorithms necessary prior to the classification of high dimensional, noisy images. PIGSCR was developed to produce fast and portable code using
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Матусевич, Олександр Павлович. "Classification Fonts." Thesis, Київський національний університет технологій та дизайну, 2017. https://er.knutd.edu.ua/handle/123456789/7344.

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Ярмак, Любов Павлівна, Любовь Павловна Ярмак, Liubov Pavlivna Yarmak, Оксана Робертівна Гладченко, Оксана Робертовна Гладченко, and Oksana Robertivna Hladchenko. "Test classification." Thesis, Сумський державний університет, 2014. http://essuir.sumdu.edu.ua/handle/123456789/34677.

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We will outline here rather briefly some of the ways tests can be classified. Understanding contrasting exam types can be helpful to teachers since tests of one kind may not always be successfully substituted for those of another kind. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/34677
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Taylor, Paul Clifford. "Classification trees." Thesis, University of Bath, 1990. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.306312.

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Bonneau, Jean-Christophe. "La classification des contrats : essai d'une analyse systémique des classifications du Code civil." Grenoble, 2010. http://www.theses.fr/2010GREND017.

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La classification des contrats telle qu'elle est énoncée aux articles 1102 et suivants du Code civil se distingue structurellement des classifications modernes lui ayant été ajoutées. Prenant au sérieux l'idée d’une approche globale de la classification, les classifications du Code civil, séparées d'un régime juridique qui ne dépend pas en réalité d'elles et de notions qui lui sont étrangères, comme la cause, ont été envisagées dans leurs rapports de logique et de complémentarité. L'existence des chaînes de classifications, nouvelle classification résultant de l'assemblage cohérent des différe
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Van, der Westhuizen Cornelius Stephanus. "Nearest hypersphere classification : a comparison with other classification techniques." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/95839.

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Thesis (MCom)--Stellenbosch University, 2014.<br>ENGLISH ABSTRACT: Classification is a widely used statistical procedure to classify objects into two or more classes according to some rule which is based on the input variables. Examples of such techniques are Linear and Quadratic Discriminant Analysis (LDA and QDA). However, classification of objects with these methods can get complicated when the number of input variables in the data become too large (􀝊 ≪ 􀝌), when the assumption of normality is no longer met or when classes are not linearly separable. Vapnik et al. (1995) introduced the
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Olin, Per. "Evaluation of text classification techniques for log file classification." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166641.

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System log files are filled with logged events, status codes, and other messages. By analyzing the log files, the systems current state can be determined, and find out if something during its execution went wrong. Log file analysis has been studied for some time now, where recent studies have shown state-of-the-art performance using machine learning techniques. In this thesis, document classification solutions were tested on log files in order to classify regular system runs versus abnormal system runs. To solve this task, supervised and unsupervised learning methods were combined. Doc2Vec was
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Anteryd, Fredrik. "Information Classification in Swedish Governmental Agencies : Analysis of Classification Guidelines." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-11493.

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Information classification deals with the handling of sensitive information, such as patient records and social security information. It is of utmost importance that this information is treated with caution in order to ensure its integrity and security. In Sweden, the Civil Contingencies Agency has established a set of guidelines for how governmental agencies should handle such information. However, there is a lack of research regarding how well these guidelines are followed as well as if the agencies have made accommodations of these guidelines of their own. This work presents the results fro
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Libros sobre el tema "Classification"

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Library of Congress. Subject Cataloging Division. Classification. 3rd ed. The Library, 1989.

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Library of Congress. Subject Cataloging Division. Classification. The Library, 1988.

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Sabzwari, Ghaniul Akram. Classification. s.n., 2005.

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Library of Congress. Cataloging Policy and Support Office. Classification. Library of Congress, 1993.

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Library of Congress. Office for Subject Cataloging Policy. Classification. 5th ed. Library of Congress, 1992.

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Haroon, Mohammed. Music classification: Schedule for colon classification. Kanishka Publishers, Distributors, 2010.

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Haroon, Mohammed. Music classification: Schedule for colon classification. Kanishka Publishers, Distributors, 2010.

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James, Mike. Classification algorithms. Wiley, 1985.

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Bandyopadhyay, Sanghamitra, and Sriparna Saha. Unsupervised Classification. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-32451-2.

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Herrera, Francisco, Francisco Charte, Antonio J. Rivera, and María J. del Jesus. Multilabel Classification. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41111-8.

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Capítulos de libros sobre el tema "Classification"

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Herrera, Francisco, Francisco Charte, Antonio J. Rivera, and María J. del Jesus. "Multilabel Classification." In Multilabel Classification. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41111-8_2.

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Herrera, Francisco, Francisco Charte, Antonio J. Rivera, and María J. del Jesus. "Introduction." In Multilabel Classification. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41111-8_1.

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Herrera, Francisco, Francisco Charte, Antonio J. Rivera, and María J. del Jesus. "Case Studies and Metrics." In Multilabel Classification. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41111-8_3.

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Herrera, Francisco, Francisco Charte, Antonio J. Rivera, and María J. del Jesus. "Transformation-Based Classifiers." In Multilabel Classification. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41111-8_4.

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Herrera, Francisco, Francisco Charte, Antonio J. Rivera, and María J. del Jesus. "Adaptation-Based Classifiers." In Multilabel Classification. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41111-8_5.

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Herrera, Francisco, Francisco Charte, Antonio J. Rivera, and María J. del Jesus. "Ensemble-Based Classifiers." In Multilabel Classification. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41111-8_6.

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Herrera, Francisco, Francisco Charte, Antonio J. Rivera, and María J. del Jesus. "Dimensionality Reduction." In Multilabel Classification. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41111-8_7.

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Herrera, Francisco, Francisco Charte, Antonio J. Rivera, and María J. del Jesus. "Imbalance in Multilabel Datasets." In Multilabel Classification. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41111-8_8.

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Herrera, Francisco, Francisco Charte, Antonio J. Rivera, and María J. del Jesus. "Multilabel Software." In Multilabel Classification. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41111-8_9.

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Abe, Shigeo. "Introduction." In Pattern Classification. Springer London, 2001. http://dx.doi.org/10.1007/978-1-4471-0285-4_1.

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Actas de conferencias sobre el tema "Classification"

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Besse, P., P. Boisson, and J. McGregor. "What Classification Rules For The Future And What Future For Classification?" In Developments in Classification & International Regulation 2007. RINA, 2007. http://dx.doi.org/10.3940/rina.dcir.2007.15.

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Bień, Jan, and Małgorzata Gładysz-Bień. "Multi-level Classification of Bridge Defects in Asset Management." In IABSE Symposium, Guimarães 2019: Towards a Resilient Built Environment Risk and Asset Management. International Association for Bridge and Structural Engineering (IABSE), 2019. http://dx.doi.org/10.2749/guimaraes.2019.1100.

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&lt;p&gt;In the paper a proposal of the unified multi-level classification of bridge defects declining condition of bridges is presented as one of the most important elements of asset management. General scheme of bridge degradation process is described with classifications of basic mechanisms of bridge degradation as well as stimulators of degradation mechanisms. Criteria of defects classification are proposed taking into account effects of activities of bridge degradation mechanisms. The proposed general conception of classification methodology of bridge defects is addressed to all types of
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Khan, Mysha, and Pushpa Bhat. "Higgs event classification using Machine Learning." In Higgs event classification using Machine Learning. US DOE, 2023. http://dx.doi.org/10.2172/1997111.

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Fadaie, Gholamreza. "The Influence of Classification on World View and Epistemology." In InSITE 2008: Informing Science + IT Education Conference. Informing Science Institute, 2008. http://dx.doi.org/10.28945/3279.

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Worldview as a kind of man's look towards the world of reality has a severe influence on his classification of knowledge. In other words one may see in classification of knowledge the unity as well as plurality. This article deals with the fact that how classification takes place in man's epistemological process. Perception and epistemology are mentioned as the key points here. Philosophers are usually classifiers and their point of views forms the way they classify things and concepts. Relationship and how one looks at it in shaping the classification scheme is critical. The classifications w
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Bruhns, H. "The New Imo Regulation For The Protection Of Fuel Tanks Affects Ship Designs." In Developments in Classification & International Regulation 2007. RINA, 2007. http://dx.doi.org/10.3940/rina.dcir.2007.12.

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Motok, M. D., and J. Jovovic. "Wave Induced Shear Force And Bending Moment For Series Of Ships - Comparison & Some Interpolation Procedures." In Developments in Classification & International Regulation 2007. RINA, 2007. http://dx.doi.org/10.3940/rina.dcir.2007.14.

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Jankowski, J., and M. Bogdaniuk. "Risk Model Used To Develop Goal-Based Standards For Ship Structures Of Single Side Bulk Carrier." In Developments in Classification & International Regulation 2007. RINA, 2007. http://dx.doi.org/10.3940/rina.dcir.2007.09.

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Rizzo, C. M., and E. Rizzuto. "A Comparison Of Common Structural Rules With Previous Class Rules." In Developments in Classification & International Regulation 2007. RINA, 2007. http://dx.doi.org/10.3940/rina.dcir.2007.01.

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Cazzulo, R., and A. Alderson. "Performance Standards Of Coatings In Ballast Tanks - Where A Class Society Could Help." In Developments in Classification & International Regulation 2007. RINA, 2007. http://dx.doi.org/10.3940/rina.dcir.2007.06.

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Moore, W., M. Arai, P. Besse, et al. "Goal-Based Standards (GBS): The International Ship & Offshore Structures Congress (ISSC) View." In Developments in Classification & International Regulation 2007. RINA, 2007. http://dx.doi.org/10.3940/rina.dcir.2007.04.

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Informes sobre el tema "Classification"

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Robinson, David Gerald. Tissue Classification. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1177377.

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SHpinev, YU S. Investment classification. Институт государства и права РАН, 2020. http://dx.doi.org/10.18411/1311-1972-2020-00011.

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Li, C., O. Havel, A. Olariu, P. Martinez-Julia, J. Nobre, and D. Lopez. Intent Classification. RFC Editor, 2022. http://dx.doi.org/10.17487/rfc9316.

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Aiken, Catherine. Classifying AI Systems. Center for Security and Emerging Technology, 2021. http://dx.doi.org/10.51593/20200025.

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This brief explores the development and testing of artificial intelligence system classification frameworks intended to distill AI systems into concise, comparable and policy-relevant dimensions. Comparing more than 1,800 system classifications, it points to several factors that increase the utility of a framework for human classification of AI systems and enable AI system management, risk assessment and governance.
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Hersey, Anne, ed. ChEMBL Assay Classification. EMBL-EBI, 2018. http://dx.doi.org/10.6019/chembl.assayclassification.

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Schau, M. Classification of granulites. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1990. http://dx.doi.org/10.4095/128123.

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Brereton, S. J. Hazard classification methodology. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/273808.

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DEPARTMENT OF THE ARMY WASHINGTON DC. Classification Management Tutorial. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada458946.

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Bogdanovic, D., B. Claise, and C. Moberg. YANG Module Classification. RFC Editor, 2017. http://dx.doi.org/10.17487/rfc8199.

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Marrs, Frank. Multiclass classification experiments. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1669069.

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