Дисертації з теми "Fingerprints Classification Data processing"
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Deng, Huimin, and 鄧惠民. "Robust minutia-based fingerprint verification." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B37036427.
Повний текст джерелаAygar, Alper. "Doppler Radar Data Processing And Classification." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609890/index.pdf.
Повний текст джерелаFernandez, Noemi. "Statistical information processing for data classification." FIU Digital Commons, 1996. http://digitalcommons.fiu.edu/etd/3297.
Повний текст джерелаVarnavas, Andreas Soteriou. "Signal processing methods for EEG data classification." Thesis, Imperial College London, 2008. http://hdl.handle.net/10044/1/11943.
Повний текст джерелаShen, Shan. "MRI brain tumour classification using image processing and data mining." Thesis, University of Strathclyde, 2004. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=21543.
Повний текст джерелаKirkin, S., and K. V. Melnyk. "Intelligent Data Processing in Creating Targeted Advertising." Thesis, National Technical University "Kharkiv Polytechnic Institute", 2017. http://repository.kpi.kharkov.ua/handle/KhPI-Press/44710.
Повний текст джерелаPinheiro, Muriel Aline. "Processing, radiometric correction, autofocus and polarimetric classification of circular SAR data." Instituto Tecnológico de Aeronáutica, 2010. http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=1083.
Повний текст джерелаALMEIDA, Marcos Antonio Martins de. "Statistical analysis applied to data classification and image filtering." Universidade Federal de Pernambuco, 2016. https://repositorio.ufpe.br/handle/123456789/25506.
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Statistical analysis is a tool of wide applicability in several areas of scientific knowledge. This thesis makes use of statistical analysis in two different applications: data classification and image processing targeted at document image binarization. In the first case, this thesis presents an analysis of several aspects of the consistency of the classification of the senior researchers in computer science of the Brazilian research council, CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico. The second application of statistical analysis developed in this thesis addresses filtering-out the back to front interference which appears whenever a document is written or typed on both sides of translucent paper. In this topic, an assessment of the most important algorithms found in the literature is made, taking into account a large quantity of parameters such as the strength of the back to front interference, the diffusion of the ink in the paper, and the texture and hue of the paper due to aging. A new binarization algorithm is proposed, which is capable of removing the back-to-front noise in a wide range of documents. Additionally, this thesis proposes a new concept of “intelligent” binarization for complex documents, which besides text encompass several graphical elements such as figures, photos, diagrams, etc.
Análise estatística é uma ferramenta de grande aplicabilidade em diversas áreas do conhecimento científico. Esta tese faz uso de análise estatística em duas aplicações distintas: classificação de dados e processamento de imagens de documentos visando a binarização. No primeiro caso, é aqui feita uma análise de diversos aspectos da consistência da classificação de pesquisadores sêniores do CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico, na área de Ciência da Computação. A segunda aplicação de análise estatística aqui desenvolvida trata da filtragem da interferência frente-verso que surge quando um documento é escrito ou impresso em ambos os lados da folha de um papel translúcido. Neste tópico é inicialmente feita uma análise da qualidade dos mais importantes algoritmos de binarização levando em consideração parâmetros tais como a intensidade da interferência frente-verso, a difusão da tinta no papel e a textura e escurecimento do papel pelo envelhecimento. Um novo algoritmo para a binarização eficiente de documentos com interferência frente-verso é aqui apresentado, tendo se mostrado capaz de remover tal ruído em uma grande gama de documentos. Adicionalmente, é aqui proposta a binarização “inteligente” de documentos complexos que envolvem diversos elementos gráficos (figuras, diagramas, etc).
Schmidt, Sven. "Quality-of-Service-Aware Data Stream Processing." Doctoral thesis, Technische Universität Dresden, 2006. https://tud.qucosa.de/id/qucosa%3A23955.
Повний текст джерелаKutzner, Kendy. "Processing MODIS Data for Fire Detection in Australia." Thesis, Universitätsbibliothek Chemnitz, 2002. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-200200831.
Повний текст джерелаDas Ziel dieser Arbeit war die Nutzung von Fernerkundungsdaten des MODIS Instruments an Bord des Satelliten Terra zur Erkennung von Buschfeuern in Australien. Das schloss die Vorverarbeitung der Daten vom Demodulator, die Bitsynchronisation und die Umpacketierung der Daten ein. IMAPP wurde genutzt um die Daten zu kalibrieren und zu geolokalisieren. Die Feuererkennung bedient sich einer Kombination von absoluten Schwellwerttests, Differenztests und Vergleichen mit dem Hintergrund. Die Ergebnisse wurden in eine rechteckige Laengen/Breitengradkarte projiziert um dem BowTie Effekt entgegenzuwirken. Die benutzten Algrorithmen wurden in C und Matlab implementiert. Es zeigte sich, dass es moeglich ist in den verfuegbaren Daten Feuer zu erkennen. Die Ergebnisse wurden mit Feuererkennungen der NASA und Feuererkennung die auf anderen Sensoren basieren verglichen und fuer sehr aehnlich befunden
Mugtussids, Iossif B. "Flight Data Processing Techniques to Identify Unusual Events." Diss., Virginia Tech, 2000. http://hdl.handle.net/10919/28095.
Повний текст джерелаPh. D.
Cho, Hansang. "Classification of functional brain data for multimedia retrieval /." Thesis, Connect to this title online; UW restricted, 2005. http://hdl.handle.net/1773/5892.
Повний текст джерелаvan, Schaik Sebastiaan Johannes. "A framework for processing correlated probabilistic data." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:91aa418d-536e-472d-9089-39bef5f62e62.
Повний текст джерелаPhillips, Rhonda D. "A Probabilistic Classification Algorithm With Soft Classification Output." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/26701.
Повний текст джерелаPh. D.
Kidane, Dawit K. "Rule-based land cover classification model : expert system integration of image and non-image spatial data." Thesis, Stellenbosch : Stellenbosch University, 2005. http://hdl.handle.net/10019.1/50445.
Повний текст джерелаENGLISH ABSTRACT: Remote sensing and image processing tools provide speedy and up-to-date information on land resources. Although remote sensing is the most effective means of land cover and land use mapping, it is not without limitations. The accuracy of image analysis depends on a number of factors, of which the image classifier used is probably the most significant. It is noted that there is no perfect classifier, but some robust classifiers achieve higher accuracy results than others. For certain land cover/uses, discrimination based only on spectral properties is extremely difficult and often produces poor results. The use of ancillary data can improve the classification process. Some classifiers incorporate ancillary data before or after the classification process, which limits the full utilization of the information contained in the ancillary data. Expert classification, on the other hand, makes better use of ancillary data by incorporating data directly into the classification process. In this study an expert classification model was developed based on spatial operations designed to identify a specific land cover/use, by integrating both spectral and available ancillary data. Ancillary data were derived either from the spectral channels or from other spatial data sources such as DEM (Digital Elevation Model) and topographical maps. The model was developed in ERDAS Imagine image-processing software, using the expert engineer as a final integrator of the different constituent spatial operations. An attempt was made to identify the Level I land cover classes in the South African National Land Cover classification scheme hierarchy. Rules were determined on the basis of expert knowledge or statistical calculations of mean and variance on training samples. Although rules could be determined by using statistical applications, such as the classification analysis regression tree (CART), the absence of adequate and accurate training data for all land cover classes and the fact that all land cover classes do not require the same predictor variables makes this option less desirable. The result of the accuracy assessment showed that the overall classification accuracy was 84.3% and kappa statistics 0.829. Although this level of accuracy might be suitable for most applications, the model is flexible enough to be improved further.
AFRIKAANSE OPSOMMING: Afstandswaameming-en beeldverwerkingstegnieke kan akkurate informasie oorbodemhulpbronne weergee. Alhoewel afstandswaameming die mees effektiewe manier van grondbedekking en grondgebruikkartering is, is dit nie sonder beperkinge nie. Die akkuraatheid van beeldverwerking is afhanklik van verskeie faktore, waarvan die beeld klassifiseerder wat gebruik word, waarskynlik die belangrikste faktor is. Dit is welbekend dat daar geen perfekte klassifiseerder is nie, alhoewel sekere kragtige klassifiseerders hoër akkuraatheid as ander behaal. Vir sekere grondbedekking en -gebruike is uitkenning gebaseer op spektrale eienskappe uiters moeilik en dikwels word swak resultate behaal. Die gebruik van aanvullende data, kan die klassifikasieproses verbeter. Sommige klassifiseerders inkorporeer aanvullende data voor of na die klassifikasieproses, wat die volle aanwending van die informasie in die aanvullende data beperk. Deskundige klassifikasie, aan die ander kant, maak beter gebruik van aanvullende data deurdat dit data direk in die klassifikasieproses inkorporeer. Tydens hierdie studie is 'n deskundige klassifikasiemodel ontwikkel gebaseer op ruimtelike verwerkings, wat ontwerp is om spesifieke grondbedekking en -gebruike te identifiseer. Laasgenoemde is behaal deur beide spektrale en beskikbare aanvullende data te integreer. Aanvullende data is afgelei van, óf spektrale eienskappe, óf ander ruimtelike bronne soos 'n DEM (Digitale Elevasie Model) en topografiese kaarte. Die model is ontwikkel in ERDAS Imagine beeldverwerking sagteware, waar die 'expert engineer' as finale integreerder van die verskillende samestellende ruimtelike verwerkings gebruik is. 'n Poging is aangewend om die Klas I grondbedekkingklasse, in die Suid-Afrikaanse Nasionale Grondbedekking klassifikasiesisteem te identifiseer. Reëls is vasgestel aan die hand van deskundige begrippe of eenvoudige statistiese berekeninge van die gemiddelde en variansie van opleidingsdata. Alhoewel reëls met behulp van statistiese toepassings, soos die 'classification analysis regression tree (CART)' vasgestel kon word, maak die afwesigheid van genoegsame en akkurate opleidingsdata vir al die grondbedekkingsklasse hierdie opsie minder aantreklik. Bykomend tot laasgenoemde, vereis alle grondbedekkingsklasse nie dieselfde voorspellingsveranderlikes nie. Die resultaat van hierdie akkuraatheidsskatting toon dat die algehele klassifikasie-akkuraatheid 84.3% was en die kappa statistieke 0.829. Alhoewel hierdie vlak van akkuraatheid vir die meeste toepassings geskik is, is die model aanpasbaar genoeg om verder te verbeter.
McKay, Cory. "Automatic genre classification of MIDI recordings." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=81503.
Повний текст джерелаRossman, Mark A. "Automated Detection of Hematological Abnormalities through Classification of Flow Cytometric Data Patterns." FIU Digital Commons, 2011. http://digitalcommons.fiu.edu/etd/344.
Повний текст джерелаTristram, Uvedale Roy. "Classification of the difficulty in accelerating problems using GPUs." Thesis, Rhodes University, 2014. http://hdl.handle.net/10962/d1012978.
Повний текст джерелаHarrison, A. "The spatial resolution of remotely sensed data and its effect on classification accuracy." Thesis, University of Reading, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.353467.
Повний текст джерелаLundgren, Andreas. "Data-Driven Engine Fault Classification and Severity Estimation Using Residuals and Data." Thesis, Linköpings universitet, Fordonssystem, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-165736.
Повний текст джерелаRobert, Denis J. "Selection and analysis of optimal textural features for accurate classification of monochrome digitized image data /." Online version of thesis, 1989. http://hdl.handle.net/1850/11364.
Повний текст джерелаPhillips, Peter. "A novel pre-processing method for the classification of data by a neural network." Thesis, University of Sussex, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.398348.
Повний текст джерелаHuang, Heng. "Land cover classification from satellite imagery, and its applications in cellular network planning." Diss., Columbia, Mo. : University of Missouri-Columbia, 2005. http://hdl.handle.net/10355/5812.
Повний текст джерелаThe entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (November 15, 2006) Vita. Includes bibliographical references.
Palanisamy, Senthil Kumar. "Association rule based classification." Link to electronic thesis, 2006. http://www.wpi.edu/Pubs/ETD/Available/etd-050306-131517/.
Повний текст джерелаKeywords: Itemset Pruning, Association Rules, Adaptive Minimal Support, Associative Classification, Classification. Includes bibliographical references (p.70-74).
Nguyen, David P. "Classification of multisite electrode recordings via variable dimension Gaussian mixtures." Thesis, Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/13929.
Повний текст джерелаLembke, Benjamin. "Bearing Diagnosis Using Fault Signal Enhancing Teqniques and Data-driven Classification." Thesis, Linköpings universitet, Fordonssystem, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-158240.
Повний текст джерелаGendron, Marlin. "Algorithms and Data Structures for Automated Change Detection and Classification of Sidescan Sonar Imagery." ScholarWorks@UNO, 2004. http://scholarworks.uno.edu/td/210.
Повний текст джерелаMajd, Farjam. "Two new parallel processors for real time classification of 3-D moving objects and quad tree generation." PDXScholar, 1985. https://pdxscholar.library.pdx.edu/open_access_etds/3421.
Повний текст джерелаPetersson, Henrik. "Multivariate Exploration and Processing of Sensor Data-applications with multidimensional sensor systems." Doctoral thesis, Linköpings universitet, Tillämpad Fysik, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-14879.
Повний текст джерелаEn sensor är en komponent som överför en fysikalisk, kemisk, eller biologisk storhet eller kvalitet till en utläsbar signal. Sensorer utgör idag en viktig del i flertalet högteknologiska produkter och sensorforskning är ett aktivt område. Komplexiteten på sensorbaserade system ökar och det blir möjligt att registrera allt er olika typer av mätsignaler. Mätsignalerna är inte alltid direkt tydbara, varvid signalbehandling blir ett väsentligt verktyg för att vaska fram den viktiga information som sökes. Signalbehandling av sensorsignaler är dessvärre inte en okomplicerad procedur och det finns många aspekter att beakta. Av denna anledning har signalbehandling och analys av sensorsignaler utvecklats till ett eget forskningsområde. Denna avhandling avhandlar metoder för att analysera komplexa multidimensionella sensorsignaler. En introduktion ges till metoder för att, utifrån mätningar, klassificera och kvantifiera egenskaper hos mätobjekt. En överblick ges av de effekter som kan uppstå på grund av imperfektioner hos sensorerna och en diskussion föres kring metoder för att undvika eller lindra de problem som dessa imperfektioner kan ge uppkomst till. Speciell vikt lägges vid sådana metoder som medför en direkt applicerbarhet och nytta för system av kemiska sensorer. I avhandlingen ingår fyra artiklar, som vart och en belyser hur de metoder som beskrivits kan användas i praktiska situationer.
Sensor,
Cheriyadat, Anil Meerasa. "Limitations of principal component analysis for dimensionality-reduction for classification of hyperspectral data." Master's thesis, Mississippi State : Mississippi State University, 2003. http://library.msstate.edu/etd/show.asp?etd=etd-11072003-133109.
Повний текст джерелаAlvarado, Mantecon Jesus Gerardo. "Towards the Automatic Classification of Student Answers to Open-ended Questions." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39093.
Повний текст джерелаLi, Yelei. "Heartbeat detection, classification and coupling analysis using Electrocardiography data." Case Western Reserve University School of Graduate Studies / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=case1405084050.
Повний текст джерелаBhonsle, Dhruvjit Vilas. "Development of an Automation Test Setup for Navigation Data Processing." Master's thesis, Universitätsbibliothek Chemnitz, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-199331.
Повний текст джерелаKim, Dae Wook. "Data-Driven Network-Centric Threat Assessment." Wright State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=wright1495191891086814.
Повний текст джерелаEklund, Martin. "Comparing Feature Extraction Methods and Effects of Pre-Processing Methods for Multi-Label Classification of Textual Data." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231438.
Повний текст джерелаDetta arbete ämnar att undersöka vilken effekt olika metoder för att extrahera särdrag ur textdata har när dessa används för att multi-tagga textdatan. Två metoder baserat på Bag of Words undersöks, närmare bestämt Count Vector-metoden samt TF-IDF-metoden. Även en metod som använder sig av word embessings undersöks, som kallas för GloVe-metoden. Multi-taggning av data kan vara användbart när datan, exempelvis musikaliska stycken eller nyhetsartiklar, kan tillhöra flera klasser eller områden. Även användandet av flera olika metoder för att förbehandla datan undersöks, såsom användandet utav N-gram, eliminering av icke-intressanta ord, samt transformering av ord med olika böjningsformer till gemensam stamform. Två olika klassificerare, en SVM samt en ANN, används för multi-taggningen genom använding utav en metod kallad Binary Relevance. Resultaten visar att valet av metod för extraktion av särdrag har en betydelsefull roll för den resulterande multi-taggningen, men att det inte finns en metod som ger bäst resultat genom alla tester. Istället indikerar resultaten att extraktionsmetoden baserad på GloVe presterar bäst när det gäller 'recall'-mätvärden, medan Bag of Words-metoderna presterar bäst gällade 'precision'-mätvärden.
Whitbread, P. J. "Multi-spectral texture : improving classification of multi-spectral images by the integration of spatial information /." Title page, abstract and contents only, 1992. http://web4.library.adelaide.edu.au/theses/09PH/09phw5792.pdf.
Повний текст джерелаOne computer disk in pocket inside back cover. System requirements for accompanying computer disk: Macintosh computer. Includes bibliographical references (leaves 148-160).
Fiebrink, Rebecca. "An exploration of feature selection as a tool for optimizing musical genre classification /." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=99372.
Повний текст джерелаVarde, Aparna S. "Graphical data mining for computational estimation in materials science applications." Link to electronic thesis, 2006. http://www.wpi.edu/Pubs/ETD/Available/etd-081506-152633/.
Повний текст джерелаMaime, Ratakane Baptista. "CHALLENGES AND OPPORTUNITIES OF ADOPTING MANAGEMENT INFORMATION SYSTEMS (MIS) FOR PASSPORT PROCESSING: COMPARATIVE STUDY BETWEEN LESOTHO AND SOUTH AFRICA." Thesis, Central University of Technology, Free State. Business Administration, 2014. http://hdl.handle.net/11462/237.
Повний текст джерелаFast and secure public service delivery is not only a necessity, but a compulsory endeavour. However, it is close to impossible to achieve such objectives without the use of Information Technology (IT). It is correspondingly important to find proper sustainability frameworks of technology. Organisations do not only need technology for efficient public service; the constant upgrading of systems and cautious migration to the newest IT developments is also equally indispensable in today’s dynamic technological world. Conversely, countries in Africa are always lagging behind in technological progresses. Such deficiencies have been identified in the passport processing of Lesotho and South Africa, where to unequal extents, problems related to systems of passport production have contributed to delays and have become fertile grounds for corrupt practices. The study seeks to identify the main impediments in the adoption of Management Information Systems (MIS) for passport processing. Furthermore, the study explores the impact MIS might have in attempting to combat long queues and to avoid long waiting periods – from application to issuance of passports to citizens. The reasonable time frame between passport application and issuance, and specific passport management systems, have been extensively discussed along with various strategies that have been adopted by some of the world’s first movers in modern passport management technologies. In all cases and stages of this research, Lesotho and South Africa are compared. The research approach of the study was descriptive and explorative in nature. As a quantitative design, a structured questionnaire was used to solicit responses in Lesotho and South Africa. It was established that both Lesotho and South Africa have somewhat similar problems – although, to a greater extent, Lesotho needs much more urgent attention. Although the processes of South Africa need to be improved, the Republic releases a passport much faster and more efficiently than Lesotho. Economic issues are also revealed by the study as unavoidable factors that always affect technological developments in Africa. The study reveals that the latest MIS for passport processing has facilitated modern, automated border-control systems and resultant e-passports that incorporate more biometric information of citizens to passports – thanks to modern RFID technologies. One can anticipate that this study will provide simple, affordable and secure IT solutions for passport processing. Key words: Information Technology (IT); Management Information Systems (MIS); E-Government; E-Passport; Biometrics; and RFID.
Sanden, Christopher, and University of Lethbridge Faculty of Arts and Science. "An empirical evaluation of computational and perceptual multi-label genre classification on music / Christopher Sanden." Thesis, Lethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer Science, c2010, 2010. http://hdl.handle.net/10133/2602.
Повний текст джерелаviii, 87 leaves ; 29 cm
Randrianarivony, Maharavo. "Geometric processing of CAD data and meshes as input of integral equation solvers." Doctoral thesis, [S.l. : s.n.], 2006. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200601972.
Повний текст джерелаVila, Duran Marius. "Information theory techniques for multimedia data classification and retrieval." Doctoral thesis, Universitat de Girona, 2015. http://hdl.handle.net/10803/302664.
Повний текст джерелаEns trobem a l’era de la informació on la majoria de les dades s’emmagatzemen en format digital. Per tant, la gestió de documents i vídeos digitals requereix el desenvolupament de tècniques eficients per a l’anàlisi automàtic. Entre elles, la captura de la similitud o dissimilitud entre diferents imatges de documents o fotogrames de vídeo és extremadament important. En aquesta tesi, analitzem, a diverses resolucions d’imatge, el comportament de tres famílies diferents de mesures basades en similitud d’imatges i aplicades a la classificació de factures. En aquests tres conjunt de mesures, el càlcul de la similitud entre dues imatges es basa, respectivament, en les diferències d’intensitat, en la informació mútua, i en la distància de compressió normalitzada. Degut a que els millors resultats s’obtenen amb les mesures basades en la informació mútua, es procedeix a investigar l’aplicació de tres generalitzacions de la informació mútua basades en Tsallis en diferents índexs entròpics. Aquestes tres generalitzacions es deriven respectivament de la distància de Kullback-Leibler, la diferència entre l’entropia i entropia condicional, i la divergència de Jensen-Shannon. En relació al processament de vídeo digital, proposem dos enfocaments diferents de teoria de la informació basats respectivament en la informació mútua de Tsallis i en la divergència de Jensen-Tsallis, per detectar els límits d’un pla cinematogràfic en una seqüència de vídeo i per seleccionar el fotograma clau més representatiu de cada pla. Finalment, l’entropia de Shannon s’ha utilitzat habitualment per quantificar la informativitat d’una imatge. El principal inconvenient d’aquesta mesura és que no té en compte la distribució espacial dels píxels. En aquesta tesi, s’analitzen quatre mesures de teoria de la informació que superen aquesta limitació. Tres d’elles (entropy rate, excess entropy i erasure entropy) consideren la imatge com un procés estocàstic estacionari, mentre que la quarta (partitional information) es basa en un canal d’informació entre les regions d’una imatge i els intervals de l’histograma
Dannenberg, Matthew. "Pattern Recognition in High-Dimensional Data." Scholarship @ Claremont, 2016. https://scholarship.claremont.edu/hmc_theses/76.
Повний текст джерелаAli, Khan Syed Irteza. "Classification using residual vector quantization." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50300.
Повний текст джерелаMaguluri, Naga Sai Nikhil. "Multi-Class Classification of Textual Data: Detection and Mitigation of Cheating in Massively Multiplayer Online Role Playing Games." Wright State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=wright1494248022049882.
Повний текст джерелаPienaar, Harrison Hursiney. "Towards a classification system of significant water resources with a case study of the Thukela river." Thesis, University of the Western Cape, 2005. http://etd.uwc.ac.za/index.php?module=etd&.
Повний текст джерелаKim, Kye Hyun 1956. "Classification of environmental hydrologic behaviors in Northeastern United States." Thesis, The University of Arizona, 1989. http://hdl.handle.net/10150/277083.
Повний текст джерелаColak, Tufan, and Rami S. R. Qahwaji. "Automated McIntosh-Based Classification of Sunspot Groups Using MDI Images." Springer, 2007. http://hdl.handle.net/10454/4091.
Повний текст джерелаThis paper presents a hybrid system for automatic detection and McIntosh-based classification of sunspot groups on SOHO/MDI white-light images using active-region data extracted from SOHO/MDI magnetogram images. After sunspots are detected from MDI white-light images they are grouped/clustered using MDI magnetogram images. By integrating image-processing and neural network techniques, detected sunspot regions are classified automatically according to the McIntosh classification system. Our results show that the automated grouping and classification of sunspots is possible with a high success rate when compared to the existing manually created catalogues. In addition, our system can detect and classify sunspot groups in their early stages, which are usually missed by human observers.
EPSRC
Eberius, Julian. "Query-Time Data Integration." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-191560.
Повний текст джерелаSong, Xiaohui. "FPGA Implementation of a Support Vector Machine based Classification System and its Potential Application in Smart Grid." University of Toledo / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1376579033.
Повний текст джерела