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Painting style-based recognition of potters

Using Convolutional Neural Network Techniques

Dados Bibliográficos

ID5362579
AutoresXiuyan Jin (Chinese Academy of Social Sciences, autor correspondente), Xin Jin (0000-0003-4590-5834), Xinwei Li (0000-0003-0555-2624, Chinese Academy of Social Sciences, autor correspondente)
Ano2025
Volume17
Fascículo5
Data de publicação2025-05-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoArchaeological and Anthropological Sciences (JOURNAL)
Identificadores do periódicoISSN: 1866-9557 • E-ISSN: 1866-9565
EditoraSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1007/s12520-025-02206-6
OpenAlexW4409295632
IdiomaEN
Referências citadas22

Archaeology · Art · Artificial neural network · Convolutional neural network · Geography · Painting · Pattern recognition (psychology · Style (visual arts · Visual arts · 3D Surveying and Cultural Heritage · Computer Science · Conservation Techniques and Studies · Cultural Heritage Materials Analysis · Artificial Intelligence

  • To Write and to Paint

    John K Papadopoulos•Panhellenes at Methone•2017

  • A scanning method for the identification of pottery forming techniques at the mesoscopic scale

    Open Access•Jon Ro, Kent D Fowler et al.•Journal of Archaeological Science…•2018

  • Detecting pitfall systems in the Suomenselkä watershed, Finland, with airborne laser scanning and artificial intelligence

    Open Access•Janne Ikäheimo•Journal of Archaeological Science…•2023

  • A compositional and technological reassessment of the function of potters’ marks on Early Bronze Age sherds from Tell el-‘Abd, Syria

    Open Access•Sara Carrión Anaya, Patrick Quinn et al.•Journal of Archaeological Science…•2024

  • Chemical variations of clays and pottery within a relatively small spatial extent

    Open Access•Pengfei Li, Ying Hu et al.•Archaeological Research in Asia•2024

  • Old recipes, new strategies

    Open Access•E Gliozzo, Pier Lorenzo Fantozzi et al.•Geoarchaeology•2020

  • Applications of deep learning to decorated ceramic typology and classification

    Open Access•L M Pawlowicz, C E Downum•Journal of Archaeological Science•2021

  • A deep variational convolutional Autoencoder for unsupervised features extraction of ceramic profiles. A case study from central Italy

    Open Access•L Cardarelli•Journal of Archaeological Science•2022

  • On quantifying and visualizing the potter's personal style

    Open Access•Ortal Harush, Naama Glauber et al.•Journal of Archaeological Science•2019

  • The Technical Style of Wallaga Pottery Making

    Open Access•Bula Sirika Wayessa•African Archaeological Review•2011

  • Individuals Among the Pots

    Enora Gandon, Thelma Coyle et al.•Ecological Psychology•2018

  • Complex raw materials and the supply system

    Open Access•B S Zhang, Xiaotong Wu et al.•Archaeometry•2021

  • Seismic vulnerability assessment of an old historical masonry building in Osijek, Croatia, using Damage Index

    Open Access•Marijana Hadzima-Nyarko, Valentina Mišetić et al.•Journal of Cultural Heritage•2017

  • Pottery vessels, technological knowledge, and potters at the Early Copper Age site of Polgár-Király-ér-part (Northeastern Hungary)

    Open Access•Eszter Solnay, Márton Szilágyi•Documenta Praehistorica•2024

  • Ancient Peruvian Potters' Marks and Their Interpretation through Ethnographic Analogy

    Open Access•Christopher B Donnan•American Antiquity•1971

  • The Ethnoarchaeology of Pottery Tempers in the Bolivian Amazon

    Open Access•Lesly García-Soto, Carla Jaimes Betancourt et al.•Ethnoarchaeology•2024

  • Mold-made potters' marks from the department of Apurimac, Peru

    Dean E Arnold•Ethnos•1972

  • New fingerprint evidence for female potters in Late Bronze Age Canaan

    Open Access•Jon Ro, Kent D Fowler et al.•Journal of Anthropological…•2023

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