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MACHINE LEARNING METHODS FOR UNESCO CHINESE HERITAGE: COMPLEXITY AND COMPARISONS.

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Bibliographic Details
Title: MACHINE LEARNING METHODS FOR UNESCO CHINESE HERITAGE: COMPLEXITY AND COMPARISONS.
Authors: Zhang, K., Teruggi, S., Fassi, F.
Source: International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences; 3/1/2022, Issue 2/W1, p543-550, 8p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 156228980
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: MACHINE LEARNING METHODS FOR UNESCO CHINESE HERITAGE: COMPLEXITY AND COMPARISONS.
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  Data: <searchLink fieldCode="AU" term="%22Zhang%2C+K%2E%22">Zhang, K.</searchLink><br /><searchLink fieldCode="AU" term="%22Teruggi%2C+S%2E%22">Teruggi, S.</searchLink><br /><searchLink fieldCode="AU" term="%22Fassi%2C+F%2E%22">Fassi, F.</searchLink>
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      – Type: doi
        Value: 10.5194/isprs-archives-XLVI-2-W1-2022-543-2022
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      – Code: eng
        Text: English
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        PageCount: 8
        StartPage: 543
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      – TitleFull: MACHINE LEARNING METHODS FOR UNESCO CHINESE HERITAGE: COMPLEXITY AND COMPARISONS.
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            NameFull: Zhang, K.
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            NameFull: Teruggi, S.
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            NameFull: Fassi, F.
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            – D: 01
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              Text: 3/1/2022
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              Y: 2022
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