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Research on machine intelligent perception of urban geographic location based on high resolution remote sensing images / Jun Chen in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 4 (April 2022)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 88 n° 4 (April 2022) . - pp 223 - 231 Titre : Research on machine intelligent perception of urban geographic location based on high resolution remote sensing images Type de document : Article/Communication Auteurs : Jun Chen, Auteur ; Cunjian Yang, Auteur ; Zengyang Yu, Auteur Année de publication : 2022 Article en page(s) : pp 223 - 231 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] base de données [Termes IGN] Chine [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] cognition [Termes IGN] détection d'objet [Termes IGN] extraction automatique [Termes IGN] géolocalisation [Termes IGN] image à haute résolution [Termes IGN] intelligence artificielle [Termes IGN] reconnaissance automatique [Termes IGN] zone urbaine Résumé : (auteur) Machine intelligent perception (MIP) provides a novel way for human beings to recognize geographical locations automatically. MIP of geographical locations enables computers to describe locations automatically and quantitatively by extracting Earth's surface features and building relationships. The earth surface fingerprint is established here by mining the relationship between spatial objects with stable characteristics extracted from urban high-resolution remote sensing images, which realizes intelligent perception of geographical location innovatively. Mask Region-based Convolutional Neural Network is used to automatically extract the spatial objects such as playgrounds, crossroads, and bridges from the images. Then, the extracted spatial objects are encoded according to the landuse type, distance, and angle of 24 nearest objects to construct urban surface fingerprint database. The urban surface fingerprint database is used to match the geographical location of spatial objects in local images so that the matching algorithm can be used for machine recognition of the geographical location of specific objects in the target image. Taking the main cities in China as the experimental area, the success rate of location perception is 92%. We have made a useful exploration in the field of MIP of geographical location, hoping to promote the development of human cognition of geographical location. Numéro de notice : A2022-285 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00017R3 Date de publication en ligne : 04/04/2022 En ligne : https://doi.org/10.14358/PERS.21-00017R3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100319 [article]

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