Explainable Artificial Intelligence (XAI) in Manufacturing

Chen, Toly

doi:10.1007/978-3-031-27961-4_1

Cited by 15 publications

(1 citation statement)

References 39 publications

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“…The first two papers investigate methods for developing and assessing data-driven models for disaggregating population cohorts into finegrained grids. The third paper contributes to the field of explainable artificial intelligence [XAI; 80,20] by explaining and confirming the decisions of the ML model on the basis of existing knowledge. The last publication promotes various geovisualisation techniques for the analysis of human migration patterns.…”

Section: Introductionmentioning

confidence: 99%

Disaggregation of population estimates at high spatial resolution with machine learning

Georgati

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In the same year, she joined the Department of Planning at Aalborg University as a research assistant. She started her PhD fellowship at Aalborg University in February 2020, working on cohort-based population estimations at the local level in European cities within the scope of the Horizon 2020 'Future Migration Scenarios for Europe' (FUME) project. Her research interests revolve around the use of programming for geospatial, urban and socio-economic analysis. She strongly believes in the potential of AI technologies to support urban development processes, making cities more sustainable and liveable for all. She enjoys experimenting with 3D visualisations, routing services and webGIS applications.

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Section: Introductionmentioning

confidence: 99%