'You Are Not My Type': An Evaluation of Classification Methods for Automatic Phytolith Identification
| Autor: | Pedro Latorre-Carmona, Javier Ruiz-Pérez, Álvar Arnaiz-González, Débora Zurro, José-Francisco Díez-Pastor |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
010506 paleontology
Standardization Computer science Feature extraction Machine learning computer.software_genre Microfossils 01 natural sciences Humans 0601 history and archaeology Instrumentation 0105 earth and related environmental sciences Informática 060102 archaeology business.industry Morphometry 06 humanities and the arts Plants Proxy Archaeology Categorization Phytolith Classification methods Artificial intelligence business computer |
| Zdroj: | Digital.CSIC. Repositorio Institucional del CSIC instname |
| ISSN: | 1435-8115 1431-9276 |
| DOI: | 10.1017/s1431927620024629 |
| Popis: | Phytoliths can be an important source of information related to environmental and climatic change, as well as to ancient plant use by humans, particularly within the disciplines of paleoecology and archaeology. Currently, phytolith identification and categorization is performed manually by researchers, a time-consuming task liable to misclassifications. The automated classification of phytoliths would allow the standardization of identification processes, avoiding possible biases related to the classification capability of researchers. This paper presents a comparative analysis of six classification methods, using digitized microscopic images to examine the efficacy of different quantitative approaches for characterizing phytoliths. A comprehensive experiment performed on images of 429 phytoliths demonstrated that the automatic phytolith classification is a promising area of research that will help researchers to invest time more efficiently and improve their recognition accuracy rate. This work was supported by the project TIN2015- 67534-P (MINECO/FEDER, UE) of the Ministerio de Economía y Competitividad of the Spanish Government, by the project BU085P17 (JCyL/FEDER, UE) of the Junta de Castilla y León (both projects co-financed through European Union FEDER funds) and by Grups de Recerca de Qualitat CaSEs – Culture and Socio-Ecological Dynamics (2017 SGR 212), AGAUR-Generalitat de Catalunya. The authors gratefully acknowledge the support of NVIDIA Corporation and its donation of the TITAN Xp GPUs used in this research. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|