English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Industrial revolutions have historically disrupted manufacturing byintroducing automation into production. Increasing automation reshapes the roleof the human worker. Advances in robotics and artificial intelligence open newfrontiers of human-machine collaboration. Such collaboration can be realizedconsidering two sub-fields of artificial intelligence: active learning andexplainable artificial intelligence. Active learning aims to devise strategiesthat help obtain data that allows machine learning algorithms to learn better.On the other hand, explainable artificial intelligence aims to make the machinelearning models intelligible to the human person. The present work firstdescribes Industry 5.0, human-machine collaboration, and state-of-the-artregarding quality inspection, emphasizing visual inspection. Then it outlineshow human-machine collaboration could be realized and enhanced in visualinspection. Finally, some of the results obtained in the EU H2020 STAR projectregarding visual inspection are shared, considering artificial intelligence,human digital twins, and cybersecurity.

Human in the AI loop via xAI and Active Learning for Visual Inspection