Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Jouni Luoma"'
Autor:
Jouni Luoma, Katerina Nastou, Tomoko Ohta, Harttu Toivonen, Evangelos Pafilis, Lars Juhl Jensen, Sampo Pyysalo
MotivationThe recognition of mentions of species names in text is a critically important task for biomedical text mining. While deep learning-based methods have made great advances in many named entity recognition tasks, results for species name reco
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::da41418b5cb802f4456e336b712317c6
https://doi.org/10.1101/2023.02.20.528934
https://doi.org/10.1101/2023.02.20.528934
This Zenodo contains the BioCreative VII Large scale DrugProt Additional Subtrackabstracts and entity annotations. Abstracts large_scale_abstracts.tsvThis filecontains plain-text, UTF8-encoded, NFC normalized DrugProt PubMed records in a tab
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::25411c99fd25dfbf9c44bc99a6284dde
Autor:
Sampo Pyysalo, Jouni Luoma
Publikováno v:
COLING
Named entity recognition (NER) is frequently addressed as a sequence classification task where each input consists of one sentence of text. It is nevertheless clear that useful information for the task can often be found outside of the scope of a sin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d064bd9fdf6b1e83425b7c3958193ac4
http://arxiv.org/abs/2006.01563
http://arxiv.org/abs/2006.01563
Publikováno v:
Tampere University
In this study, we propose and evaluate new methods for automatic extraction of the brain surface and the mid-sagittal plane from functional positron emission tomography (PET) images. Designing methods for these segmentation tasks is challenging becau
Autor:
Apidianaki, Marianna1 (AUTHOR) marapi@seas.upenn.edu
Publikováno v:
Computational Linguistics. Jun2023, Vol. 49 Issue 2, p465-523. 59p.
Publikováno v:
ACM Transactions on Information Systems; Mar2024, Vol. 42 Issue 2, p1-33, 33p
Multi-SimLex: A Large-Scale Evaluation of Multilingual and Crosslingual Lexical Semantic Similarity.
Autor:
Vulić, Ivan1 (AUTHOR) iv250@cam.ac.uk, Baker, Simon1 (AUTHOR) sb895@cam.ac.uk, Ponti, Edoardo Maria1 (AUTHOR) ep490@cam.ac.uk, Petti, Ulla1 (AUTHOR) ump20@cam.ac.uk, Leviant, Ira2 (AUTHOR) ira.leviant@campus.technion.ac.il, Wing, Kelly1 (AUTHOR) lkw33cam@gmail.com, Majewska, Olga1 (AUTHOR) om304@cam.ac.uk, Bar, Eden2 (AUTHOR) edenb@campus.technion.ac.il, Malone, Matt1 (AUTHOR) mm2289@cam.ac.uk, Poibeau, Thierry3 (AUTHOR) thierry.poibeau@ens.fr, Reichart, Roi2 (AUTHOR) roiri@ie.technion.ac.il, Korhonen, Anna1 (AUTHOR) alk23@cam.ac.uk
Publikováno v:
Computational Linguistics. Dec2020, Vol. 46 Issue 4, p847-897. 51p.
Autor:
Luoma, Jouni, Nastou, Katerina, Ohta, Tomoko, Toivonen, Harttu, Pafilis, Evangelos, Jensen, Lars Juhl, Pyysalo, Sampo
Publikováno v:
Bioinformatics; Jun2023, Vol. 39 Issue 6, p1-8, 8p
Autor:
Schneider, Britta
Publikováno v:
Signs & Society; Fall2022, Vol. 10 Issue 3, p362-387, 26p
Autor:
Sudharsan Ravichandiran
Kickstart your NLP journey by exploring BERT and its variants such as ALBERT, RoBERTa, DistilBERT, VideoBERT, and more with Hugging Face's transformers libraryKey FeaturesExplore the encoder and decoder of the transformer modelBecome well-versed with