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CHNT 25, 2020-Abstracts

Wednesday, November 4, 2020 Opening: Matti BUNZL, Director of the Wien MUSEUM, Vienna Austria Keynote 1 Eslam NOFAL, The Netherlands: Phygital Heritage ——————————————————————————————————————- Sessions AI methods for digital humanities – New pathways towards Cultural HeritageChairs: Piotr KUROCZYNSKI | Günther GÖRZ | Christoph SCHLIEDER, Germany Nikolaos MYRIDIS | Dimitra SARAKATSIANOU, Greece: Climax: A historical script΄s AI transformation for human behavioural estimation (0,2 MB) Amelie DORN | Gerda KOCH | Renato ROCHA SOUZA, Austria | Yalemisew ABGAZ, Ireland: Classification of Historic Food Images – a pilot experiment on the example of the ChIA project (PDF 0,4 MB) F. Michael BARTLETT | William J. TURKEL, Canada: Digital Analysis of Historic Bridge Images Piotr KUROCZYŃSKI | Peggy GROSSE, Germany: Ontology for Scientific Documentation of source-based 3D reconstruction of architecture (PDF 0,8 MB) Andreas NOBACK | Lars Oliver GROBE, Germany: Preparing the past for the future: Curating a daylight simulation model of Hagia Sophia for modern data infrastructures (0,3 MB) ——————————————————————————————————————- Machine Learning In ArchaeometryChair: Johannes TINTNER | Bernhard SPANGL | Michael MELCHER, Austria Bashir KAZIMI | Katharina MALEK | Frank THIEMANN | Monika SESTER, Germany: Effectiveness of DTM Derivatives for Object Detection Using Deep Learning (2 MB) Johannes TINTNER | Bernhard SPANGL | Michael MELCHER, Austria: MD-Dating – Age estimation of wood via infrared spectroscopy and random forest modelling (PDF 0,5 MB) Bernhard SPANGL | Johannes TINTNER | Michael MELCHER, Austria: MD dating – the statistical theory behind (0,1 MB) ——————————————————————————————————————- AI, ML and DL in satellite, aerial and ground based remote sensingChairs: Apostolos SARRIS, Greece | Melda KÜÇÜKDEMİRCİ, Turkey | Tuna KALAYCI, The Netherlands Immo TRINKS | Alois HINTERLEITNER | Mario WALLNER | Klaus LÖCKER | Alexander BORNIK | Johannes HÖLLER |Matthias KUCERA |Roland FILZWIESER | Hannes SCHIEL| Tanja TRAUSMUTH| Alexandra VONKILCH| Jona SCHLEGEL| David RUSS| Wolfgang NEUBAUER, Austria: Towards an automated analysis of near-surface geophysical archaeological prospection data (1,4 MB) Julien WOLF | Finnegan POPE-CARTER | Paul JOHNSON, United Kingdom: Mag-Net: Improving magnetometer interpretation workflows with semantic segmentation (PDF 0,8 MB) Juergen LANDAUER | Wouter VERSCHOOF-VAN DER VAART, Germany: CarcassonNet: A Deep Learning Approach for Mapping Hollow Roads in LiDAR Data (PDF 0,7 MB) Hassan EL HAJJ, Germany: Automating Archaeological Site...

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Johannes TINTNER

Senior scientist at the Institute of Physics and Material Sciences, University of Natural Resources and Life Sciences, Vienna. Specialist since 15 years in aging processes of organic matter, archaeometry, infrared spectroscopy and thermal analysis. After his habilitation in the field of environmental sciences he contributed groundbreaking research on dating by means of molecular decay based on machine learning methods. His research covers a wide range of organic materials including wood, straw in earthen architecture, paper, charcoal, hair, and bones. He holds collaborations with prehistoric and medieval archaeologists, historians, dendrochronologists, soil scientists and palaeoecologists, not only in Austria, but also international. He is speaker of BOKU research groups in heritage science at the platform Heritage Science...

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CHNT 25, 2020 – Permissions

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The Babylonian Engine

Human-Machine collaboration for restoring ancient Mesopotamian heritage Ethan Fetaya FETAYA 1 | Shai GORDIN 2(1 Bar-Ilan University, Ramat Gan | 2 Ariel University Faculty of Social Sciences and Humanities, Ariel, Israel) Abstract: The documentary sources for the political, economic, and social history of ancient Mesopotamia (modern Iraq) constitute hundreds of thousands of clay tablets inscribed in the cuneiform script. Most tablets are damaged, leaving gaps in the texts written on them, and the missing portions must be restored by experts. In our talk, we will present a new open-source initiative called the Babylonian Engine, a Digital Humanities project that aims to reconstruct the ancient Babylonian society, environment and landscape using philological data and Machine Learning algorithms. We will discuss available digitized texts in Akkadian and how they can be used for training advanced machine-learning algorithms to restore daily economic and administrative documents from Babylonia under the rule of the Persian empire (6th to 4th centuries BCE). As the amount of digitized texts grows, the model can be trained to restore damaged texts belonging to other genres, such as scientific or literary texts. Therefore, this is a first step for a large-scale reconstruction of a lost ancient heritage, by creating a human-machine interface for the historical sciences and the...

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