Deep learning-based morphological classification of ceramics: A case study of 3D point cloud analysis for Sue ware, Japan

2026/01/16 by Wataru Tatsuda, Ryo Hori, Kimiyasu Morikawa +1 · 1 voice
Arts and Humanities · Computer Science · Engineering · #3D Shape Modeling and Analysis #Cultural Heritage Materials Analysis #Image Processing and 3D Reconstruction

paper · doi:10.1016/j.jas.2026.106472

openalex publication_date 2026/01/16 · crossref created 2026/01/16 · openalex created_date 2026/01/17 · crossref issued 2026/03/01 · crossref published 2026/03/01 · crossref published-print 2026/03/01 · crossref deposited 2026/03/20 · crossref indexed 2026/04/16 · openalex updated_date 2026/06/11

Citations

• On the Universality of Rotation Equivariant Point Cloud Networks
• Dynamic Graph CNN for Learning on Point Clouds
• Dynamic Graph CNN for Learning on Point Clouds
• Attention Is All You Need
• PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
• "Why Should I Trust You?": Explaining the Predictions of Any Classifier

Discussions

• I am pleased to share that our paper has been published in the Journal of Archaeological Science! A big thank you to the UCL Institute of Archaeology for featuring our work! Thanks to the Institute’s [bsky, 2 points, 0 comments]