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Spectral fuzzy classification: An application

dc.contributor.authorDel Amo, Ana
dc.contributor.authorMontero De Juan, Francisco Javier
dc.contributor.authorFernández, Angela
dc.contributor.authorLópez, Marina
dc.contributor.authorTordesillas, José Manuel
dc.contributor.authorBiging, Greg
dc.date.accessioned2023-06-20T17:00:20Z
dc.date.available2023-06-20T17:00:20Z
dc.date.issued2002
dc.description.abstractGeographical information (including remotely sensed data) is usually imprecise, meaning that the boundaries between different phenomena are fuzzy. In fact, many classes in nature show internal gradual differences in species, health, age, moisture, as well other factors. If our classification model does not acknowledge that those classes are heterogeneous, and crisp classes are artificially imposed, a final careful analysis should always search for the consequences of such an unrealistic assumption. In this correspondence, we consider the unsupervised algorithm presented in [3], and its application to a real image in Sevilla province (south Spain). Results are compared with those obtained from the ERDAS ISO-DATA classification program on the same image, showing the accuracy of our fuzzy approach. As a conclusion, it is pointed out that whenever real classes are natural fuzzy classes, with gradual transition between classes, then its fuzzy representation will be more easily understood-and therefore accepted-by users.en
dc.description.departmentDepto. de Estadística e Investigación Operativa
dc.description.facultyFac. de Ciencias Matemáticas
dc.description.refereedTRUE
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/16777
dc.identifier.citationKachroo, P., Shedied, S.A., Vanlandingham, H.: Pursuit evasion: the herding noncooperative dynamic game - the stochastic model. IEEE Trans. Syst., Man, Cybern. C. 32, 37-42 (2002). https://doi.org/10.1109/TSMCC.2002.1009131
dc.identifier.doi10.1109/TSMCC.2002.1009131
dc.identifier.issn1094-6977
dc.identifier.officialurlhttps//doi.org/10.1109/TSMCC.2002.1009131
dc.identifier.relatedurlhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1009135
dc.identifier.urihttps://hdl.handle.net/20.500.14352/57610
dc.issue.number1
dc.journal.titleIEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
dc.language.isoeng
dc.page.final48
dc.page.initial42
dc.publisherIEEE-Inst Electrical Electronics Engineers Inc
dc.rights.accessRightsrestricted access
dc.subject.cdu510.64
dc.subject.cdu004.8
dc.subject.keywordFuzzy classification
dc.subject.keywordOutranking models
dc.subject.keywordRemote sensing
dc.subject.ucmInteligencia artificial (Informática)
dc.subject.ucmLógica simbólica y matemática (Matemáticas)
dc.subject.unesco1203.04 Inteligencia Artificial
dc.subject.unesco1102.14 Lógica Simbólica
dc.titleSpectral fuzzy classification: An applicationen
dc.typejournal article
dc.volume.number32
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