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The analysis of such data presents many different problems to classic problems in the field of computer vision, where input data is most commonly acquired using sensors which capture visible wavelengths and is generally Euclidean in nature. While working with data which is inherently non-euclidean presents many challenges, this research aims to consider, among other techniques, the merits of exciting developments in geometric deep learning for the analysis of multimodal, remotely-sensed data. \nThe following EPSRC Research Areas have been identified as topics which this research will engage with: Artificial intelligence technologies; Built environment; Data signal processing; Image and vision computing; Infrastructure and urban systems; Statistics and applied probability; Structural engineering.","granted":{"currency":"GBP","totalCost":0.0,"fundedAmount":0.0},"h2020Programmes":null,"funding":{"funder":{"id":"ukri________::UKRI","shortname":"UKRI","name":"UK Research and Innovation","jurisdiction":{"code":"GB","label":"United 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