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learning has strong potential for computer vision, from hyperbolic image segmentation [2] to hyperbolic tree embeddings [3] and hyperbolic vision-language models [4,5]. [1] Nickel, Maximillian, and Douwe
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proposal. This PhD will evaluate the efficacy and suitability of digital image collection and analysis for beach litter characterisation on heavily-littered coastlines, in partnership with community groups
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geometry altogether and operate in hyperbolic space. Our lab has published multiple papers showing that hyperbolic deep learning has strong potential for computer vision, from hyperbolic image segmentation
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interaction. Plant performance will be assessed by measuring life history traits and fitness and using hyperspectral imaging of both roots and shoots. The performance of both parasites will also be quantified
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parasite and warming in different combinations and sequences), and their interaction. Plant performance will be assessed by measuring life history traits and fitness and using hyperspectral imaging of both
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Job Description If you are passionate about stem cell biology and want to make a real difference for patients suffering from vision loss, this PhD position is for you. At DTU Health Tech, we offer a
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related disciplines Quantitative imaging, data analysis, or computer vision Numerical modeling of biological systems or continuum mechanics Machine learning/AI, particularly explainable AI (XAI) Hands
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This PhD project focuses on advancing computer vision and edge-AI technology for real-time marine monitoring. In collaboration with CEFAS (the Centre for Environment, Fisheries, and Aquaculture
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DTU Tenure Track Researcher in Low-Noise Supercontinuum Lasers and Supercontinuum Laser based Opt...
(OCT) imaging, then we have the ideal opportunity for you. Come and be a part of the “Table-Top Synchrotron” project and one of the world’s strongest groups in this field in our quest to develop
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at