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unit and then pre-processed data used as the input of the deep learning algorithm. The research will employ the SafeML tool (a novel open-source safety monitoring tool) to measure the statistical
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sensors systems and UAVs at different scales. In particular, we will combine borehole and surface GPR as well as small-scale EMI measurements with root and shoot observations in controlled experiments
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using electromagnetic induction (EMI), and ground penetrating radar (GPR) will be combined with soil sensors systems and UAVs at different scales. In particular, we will combine borehole and surface GPR
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behavioral component as it would be interesting to study how consumers perceive algorithmic discrimination of different kinds and how companies can mitigate negative perceptions. During their PhD
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with bigger models and larger datasets. A critical issue is the embedding of hierarchies, for which a different geometry is better suited, namely hyperbolic geometry. Seminal works have shown
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in crops, (2) how different radar polarisations (e.g. VV, VH, cross-pol) affect sensitivity to crop growth and condition, and (3) how to disentangle the effects of soil moisture variations from
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data are needed to enhance our understanding of sources, pathways and impact of litter. Cefas is developing a visible light (VL) deep learning (DL) algorithm and collected a large 89 litter category
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different approaches, the most prevalent is polygraph testing which infers deception through the measurement and analysis of physiological responses (e.g., blood pressure, electrodermal activity). However
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) develop novel performance metrics combining accuracy and explainability, to be tested across different AI model types; (2) devise new algorithms for selecting models optimised for holistic performance
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across Scotland’s west coast. It will evaluate the practicality of different image capture techniques and the potential of different sensor types (e.g., RGB, multispectral) to generate beach litter images