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Insects: classification chart showing various varieties and stages of development, including larvae, beetles and butterflies. Coloured lithograph, 1850/1870?
Previously, we introduced you to the Europeana Foundation’s image classification pilot, for which we had selected a target vocabulary and gathered a dataset to train a model to classify images from digitised cultural heritage. In this post, we analyse the results of the training, identify some challenges with our current approach, and propose future lines of work!
Mollusc shells: classification chart showing 132 varieties, with a diagram below outlining details of the three main shapes. Coloured lithograph, 1830/1860?
With lowered barriers to access and the development of new practices for Artificial Intelligence (AI), it’s no surprise that AI-related activities in the cultural heritage sector are increasing - a topic in focus on this month on Europeana Pro. In this post, we share work taking place at the Europeana Foundation to create an image classification pilot which uses computer vision algorithms to improve metadata in our records.
With lowered barriers to access and the development of new practices for Artificial Intelligence (AI), it’s no surprise that AI-related activities in the cultural heritage sector are increasing. In this post, we are delighted to introduce the winning projects from EuropeanaTech’s first Challenge for Europeana AI/ML Datasets!
With lowered barriers to access and the development of new practices for Artificial Intelligence (AI), it’s no surprise that AI-related activities in the cultural heritage sector are increasing. EuropeanaTech Community Manager Gregory Markus introduces a Europeana Pro news theme on the topic!
EuropeanaTech is excited to invite proposals for the assembly of Artificial Intelligence/ Machine Learning (AI/ML) datasets drawn from the extensive collections on the Europeana website. Two proposals will be selected to receive a financial stipend of €2,500 each, to support the production, documentation and publication of the datasets.
