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Open Access research that better understands changing marine ecologies...

Strathprints makes available scholarly Open Access content by researchers in the Department of Mathematics & Statistics.

Mathematics & Statistics hosts the Marine Population Modelling group which is engaged in research into topics surrounding marine resource modelling and ecology. Recent work has included important developments in the population modelling of marine species.

Explore the Open Access research of Mathematics & Statistics. Or explore all of Strathclyde's Open Access research...

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Number of items: 4.

Czerkawski, Mikolaj and Upadhyay, Priti and Davison, Christopher and Atkinson, Robert and Michie, Craig and Andonovic, Ivan and Macdonald, Malcolm and Cardona, Javier and Tachtatzis, Christos (2024) Multi-modal convolutional parameterisation network for guided image inverse problems. Journal of Imaging, 10 (3). 69. ISSN 2313-433X

Czerkawski, Mikolaj and Upadhyay, Priti and Davison, Christopher and Werkmeister, Astrid and Cardona, Javier and Atkinson, Robert and Michie, Craig and Andonovic, Ivan and Macdonald, Malcolm and Tachtatzis, Christos (2022) Correction: Czerkawski et al. Deep internal learning for inpainting of cloud-affected regions in satellite umagery. Remote Sens. 2022, 14, 1342. Remote Sensing, 14 (24). 6324. ISSN 2072-4292

Czerkawski, Mikolaj and Upadhyay, Priti and Davison, Christopher and Werkmeister, Astrid and Cardona, Javier and Atkinson, Robert and Michie, Craig and Andonovic, Ivan and Macdonald, Malcolm and Tachtatzis, Christos (2022) Deep internal learning for inpainting of cloud-affected regions in satellite imagery. Remote Sensing, 14 (6). 1342. ISSN 2072-4292

Upadhyay, Priti and Czerkawski, Mikolaj and Davison, Christopher and Cardona, Javier and Macdonald, Malcolm and Andonovic, Ivan and Michie, Craig and Atkinson, Robert and Papadopoulou, Nikela and Nikas, Konstantinos and Tachtatzis, Christos (2022) A flexible multi-temporal and multi-modal framework for Sentinel-1 and Sentinel-2 analysis ready data. Remote Sensing, 14 (5). 1120. ISSN 2072-4292

This list was generated on Thu Dec 19 00:41:36 2024 GMT.