DECIMER.ai: an open platform for automated optical chemical structure identification, segmentation and recognition in scientific publications

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22310%2F23%3A43927138" target="_blank" >RIV/60461373:22310/23:43927138 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.nature.com/articles/s41467-023-40782-0" target="_blank" >https://www.nature.com/articles/s41467-023-40782-0</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41467-023-40782-0" target="_blank" >10.1038/s41467-023-40782-0</a>

Jazyk výsledku

angličtina

Název v původním jazyce

DECIMER.ai: an open platform for automated optical chemical structure identification, segmentation and recognition in scientific publications

Popis výsledku v původním jazyce

The number of publications describing chemical structures has increased steadily over the last decades. However, the majority of published chemical information is currently not available in machine-readable form in public databases. It remains a challenge to automate the process of information extraction in a way that requires less manual intervention - especially the mining of chemical structure depictions. As an open-source platform that leverages recent advancements in deep learning, computer vision, and natural language processing, DECIMER.ai (Deep lEarning for Chemical IMagE Recognition) strives to automatically segment, classify, and translate chemical structure depictions from the printed literature. The segmentation and classification tools are the only openly available packages of their kind, and the optical chemical structure recognition (OCSR) core application yields outstanding performance on all benchmark datasets. The source code, the trained models and the datasets developed in this work have been published under permissive licences. An instance of the DECIMER web application is available at https://decimer.ai.

Název v anglickém jazyce

DECIMER.ai: an open platform for automated optical chemical structure identification, segmentation and recognition in scientific publications

Popis výsledku anglicky

The number of publications describing chemical structures has increased steadily over the last decades. However, the majority of published chemical information is currently not available in machine-readable form in public databases. It remains a challenge to automate the process of information extraction in a way that requires less manual intervention - especially the mining of chemical structure depictions. As an open-source platform that leverages recent advancements in deep learning, computer vision, and natural language processing, DECIMER.ai (Deep lEarning for Chemical IMagE Recognition) strives to automatically segment, classify, and translate chemical structure depictions from the printed literature. The segmentation and classification tools are the only openly available packages of their kind, and the optical chemical structure recognition (OCSR) core application yields outstanding performance on all benchmark datasets. The source code, the trained models and the datasets developed in this work have been published under permissive licences. An instance of the DECIMER web application is available at https://decimer.ai.

Druh

J_ost - Ostatní články v recenzovaných periodicích

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Nature Communications

ISSN

2041-1723

e-ISSN

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Svazek periodika

Neuveden

Číslo periodika v rámci svazku

08.2023

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

18

Strana od-do

"nestrankovano"

Kód UT WoS článku

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EID výsledku v databázi Scopus

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