This paper is in the following e-collection/theme issue:

New Methods (945) Natural Language Processing (693) Food Sciences and Nutrition Engineering (54) Ontologies, Classifications, and Coding (239) Machine Learning (1465) Data Science (270)

Published on in Vol 23, No 8 (2021): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28229, first published .
A Fine-Tuned Bidirectional Encoder Representations From Transformers Model for Food Named-Entity Recognition: Algorithm Development and Validation

A Fine-Tuned Bidirectional Encoder Representations From Transformers Model for Food Named-Entity Recognition: Algorithm Development and Validation

A Fine-Tuned Bidirectional Encoder Representations From Transformers Model for Food Named-Entity Recognition: Algorithm Development and Validation

Authors of this article:

Riste Stojanov1 Author Orcid Image ;   Gorjan Popovski2, 3 Author Orcid Image ;   Gjorgjina Cenikj2, 3 Author Orcid Image ;   Barbara Koroušić Seljak2 Author Orcid Image ;   Tome Eftimov2 Author Orcid Image
Article Authors Cited by (14) Tweetations (7) Metrics

Riste Stojanov   1 * , PhD ;   Gorjan Popovski   2, 3 * , MSc ;   Gjorgjina Cenikj   2, 3 * , BSc ;   Barbara Koroušić Seljak   2 * , PhD ;   Tome Eftimov   2 * , PhD

1 Faculty of Computer Science and Engineering, Ss Cyril and Methodius, University- Skopje, Skopje, North Macedonia

2 Computer Systems Department, Jožef Stefan Institute, Ljubljana, Slovenia

3 Jožef Stefan International Postgraduate School, Ljubljana, Slovenia

*all authors contributed equally

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