<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1390-9274</journal-id>
<journal-title><![CDATA[Estoa. Revista de la Facultad de Arquitectura y Urbanismo de la Universidad de Cuenca]]></journal-title>
<abbrev-journal-title><![CDATA[Estoa]]></abbrev-journal-title>
<issn>1390-9274</issn>
<publisher>
<publisher-name><![CDATA[Centro de Investigación de la Facultad de Arquitectura y Urbanismo de la Universidad de Cuenca]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1390-92742022000200097</article-id>
<article-id pub-id-type="doi">10.18537/est.v011.n022.a06</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Transferencia recíproca de información y estilo entre los mapas históricos de Estambul de Pervititch y las vistas satelitales mediante el aprendizaje automático]]></article-title>
<article-title xml:lang="en"><![CDATA[Reciprocal style and information transfer between historical Istanbul Pervititch Maps and satellite views using machine learning]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Alaçam]]></surname>
<given-names><![CDATA[Sema]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Karadag]]></surname>
<given-names><![CDATA[Ilker]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Güzelci]]></surname>
<given-names><![CDATA[Orkan Zeynel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Istanbul Technical University  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Turkey</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Manisa Celal Bayar University  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Turquía</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,University of Porto  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Portugal</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2022</year>
</pub-date>
<volume>11</volume>
<numero>22</numero>
<fpage>97</fpage>
<lpage>113</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.senescyt.gob.ec/scielo.php?script=sci_arttext&amp;pid=S1390-92742022000200097&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.senescyt.gob.ec/scielo.php?script=sci_abstract&amp;pid=S1390-92742022000200097&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.senescyt.gob.ec/scielo.php?script=sci_pdf&amp;pid=S1390-92742022000200097&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen: Los mapas históricos contienen datos importantes sobre el carácter cultural, social y urbano de las ciudades. La mayoría de los mapas históricos utilizan notaciones específicas que difieren de los mapas de uso común en la actualidad. Por lo tanto, la conversión de datos de mapas históricos a formatos de mapas recientes puede considerarse una actividad que requiere mucha mano de obra. Este artículo tiene como objetivo exponer cómo se puede utilizar una técnica de aprendizaje automático (machine learning), para transformar mapas antiguos de Estambul en datos espaciales que simulan vistas de satélite modernas (SVs) a través de un marco de trabajo de mapas recíprocos. Con este objetivo, se utilizan los mapas de Estambul de Jacques Pervititch (IPMs) de 1922-1945 y las vistas de satélite actuales para probar y evaluar el marco propuesto. El estudio consta de dos etapas: (i) el estilo y la transferencia de información de IPMs a SVs, (ii) de SVs a IPMs con CycleGAN (un tipo de red adversarial generativa). Los resultados iniciales muestran que el marco de trabajo propuesto puede trasladar atributos tales como áreas verdes, técnicas y materiales constructivos, y etiquetas.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: Historical maps contain significant data on the cultural, social, and urban character of cities. However, most historical maps utilize specific notation methods that differ from those commonly used today and converting these maps to more recent formats can be highly labor-intensive. This study is intended to demonstrate how a machine learning (ML) technique can be used to transform old maps of Istanbul into spatial data that simulates modern satellite views (SVs) through a reciprocal map conversion framework. With this aim, the Istanbul Pervititch Maps (IPMs) made by Jacques Pervititch in 1922-1945 and current SVs were used to test and evaluate the proposed framework. The study consists of a style and information transfer in two stages: (i) from IPMs to SVs, and (ii) from SVs to IPMs using CycleGAN (a type of generative adversarial network). The initial results indicate that the proposed framework can transfer attributes such as green areas, construction techniques/ materials, and labels/tags.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Istanbul Pervititch Maps]]></kwd>
<kwd lng="en"><![CDATA[artificial intelligence]]></kwd>
<kwd lng="en"><![CDATA[machine learning]]></kwd>
<kwd lng="en"><![CDATA[semantic segmentation]]></kwd>
<kwd lng="en"><![CDATA[CycleGAN]]></kwd>
<kwd lng="es"><![CDATA[mapas de Estambul de Pervititch]]></kwd>
<kwd lng="es"><![CDATA[inteligencia artificial]]></kwd>
<kwd lng="es"><![CDATA[aprendizaje automático]]></kwd>
<kwd lng="es"><![CDATA[segmentación semántica]]></kwd>
<kwd lng="es"><![CDATA[CycleGAN]]></kwd>
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</article-meta>
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