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Field
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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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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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to develop Computer Vision algorithm and Interfaces for collaborations with Historians teams. Specifically, the research will focus on structured data with clear repeated patterns, such as characters in a text
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to track how the prevalences of different strains in a mixed sample change over time. Your role: You will develop and implement algorithms to find, quantify and track mutations in evolving populations
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designed to meet multiple needs in marine biodiversity monitoring. The project aims to develop embedded novel deep learning and computer vision algorithms to extend the system’s capabilities to classify
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. For example, we would like to be able to track how the prevalences of different strains in a mixed sample change over time. Your role: You will develop and implement algorithms to find, quantify and track
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persuasion, how different types of people cope and are affected, and how we can develop remedies to reduce negative consequences. By doing so you disentangle possible (not mutually exclusive) mechanisms
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; they make sense to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project
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for achieving the desired mechanical and functional properties of the final structures. Unlike conventional DIW systems or the recently developed FL3DP technique that operate on fixed Cartesian coordinate with a
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advance scholarship on who is most often exposed to algorithmic persuasion, how different types of people cope and are affected, and how we can develop remedies to reduce negative consequences. By doing so