Automated detection and classification of multi-cell Phytoliths using Deep Learning-Based Algorithms
Bibliographic Data
| ID | 11900424 |
|---|---|
| Authors | Iban Berganzo-Besga, Iban Berganzo‐besga (0000-0002-6161-2452, corresponding author), Hector A Orengo (0000-0002-9385-2370), Felipe Lumbreras (0000-0003-2887-8053), Paloma Aliende, Monica N Ramsey (0000-0002-1223-1725) |
| Year | 2022 |
| Volume | 148 |
| Pages | 105654-105654 |
| Publication date | 2022-10-10 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Archaeological Science (JOURNAL) |
| Journal identifiers | ISSN: 0305-4403 • E-ISSN: 1095-9238 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.jas.2022.105654 |
| OpenAlex | W4303945557 |
| Language | EN |
| Citations received | 10 |
| References cited | 13 |
Algorithm · Deep learning · Pattern recognition (psychology · Archaeology and ancient environmental studies · Computer Science · Image Processing and 3D Reconstruction · Silicon Effects in Agriculture · Artificial Intelligence
Experts against automation? Comparing artificial intelligence and human identifications of multi-cell cereal husk phytoliths
Ecological flexibility
Best practices for the application of computer vision-based machine learning in archaeology
High-performance 3D morphometrics via deep learning and tabular foundation models
Scaling up phytolith preparation protocols for big data
Deep learning-based identification of carbonized seeds
An AI-assisted workflow for object detection and data collection from archaeological catalogues
Automated starch granule classification using high-throughput microscopy and machine learning
Potential of SEM and Deep Learning in Archaeobotanical Identification of Ancient Wheat Varieties
Ecological-cultural inheritance in the wetlands
Preliminary Identification of Silica Skeletons from Near Eastern Archaeological Sites
Phytoliths Analysis for the Discrimination of Foxtail Millet (Setaria italica) and Common Millet (Panicum miliaceum)
International Code for Phytolith Nomenclature (ICPN) 2.0
Methodological concerns for analysis of phytolith assemblages
Developing the ArchAide application
New developments in drone‐based automated surface survey
Phytolith analysis for the identification of barnyard millet (Echinochloa sp.) and its implications
Phytolith identification criteria for foxtail and broomcorn millets
| Unique citing works | 10 |
|---|---|
| Citations per year | 3.33 |
| Citation span | 2023 - 2026 (4) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 10 |