Sahraoui M., Sklab Youcef, Pignal M., Vignes Lebbe R., Guigue V. (2023). Leveraging multimodality for biodiversity data : exploring joint representations of species descriptions and specimen images using CLIP. Biodiversity Information Science and Standards, 7, e112666 [4 p.]. ISSN 2535-0897.
Titre du document
Leveraging multimodality for biodiversity data : exploring joint representations of species descriptions and specimen images using CLIP
Année de publication
2023
Type de document
Colloque
Auteurs
Sahraoui M., Sklab Youcef, Pignal M., Vignes Lebbe R., Guigue V.
Source
Biodiversity Information Science and Standards, 2023,
7, e112666 [4 p.] ISSN 2535-0897
In recent years, the field of biodiversity data analysis has witnessed significant advancements, with a number of models emerging to process and extract valuable insights from various data sources. One notable area of progress lies in the analysis of species descriptions, where structured knowledge extraction techniques have gained prominence. These techniques aim to automatically extract relevant information from unstructured text, such as taxonomic classifications and morphological traits. (Sahraoui et al. 2022, Sahraoui et al. 2023) By applying natural language processing (NLP) and machine learning methods, structured knowledge extraction enables the conversion of textual species descriptions into a structured format, facilitating easier integration, searchability, and analysis of biodiversity data.
Plan de classement
Etudes, transformation, conservation du milieu naturel [082]
;
Informatique [122]
