The effect of particle properties on the depth profile of buoyant plastics in the ocean M Kooi, J Reisser, B Slat, FF Ferrari, MS Schmid, S Cunsolo, R Brambini, ... Scientific reports 6 (1), 33882, 2016 | 270 | 2016 |
The LOKI underwater imaging system and an automatic identification model for the detection of zooplankton taxa in the Arctic Ocean MS Schmid, C Aubry, J Grigor, L Fortier Methods in Oceanography 15, 129-160, 2016 | 53 | 2016 |
Lipid load triggers migration to diapause in Arctic Calanus copepods—insights from underwater imaging MS Schmid, F Maps, L Fortier Journal of Plankton Research 40 (3), 311-325, 2018 | 45 | 2018 |
Seasonal observations and machine-learning-based spatial model predictions for the common raven (Corvus corax) in the urban, sub-arctic environment of … AP Baltensperger, TC Mullet, MS Schmid, GRW Humphries, L Kövér, ... Polar Biology 36, 1587-1599, 2013 | 45 | 2013 |
Prey and predator overlap at the edge of a mesoscale eddy: Fine-scale, in-situ distributions to inform our understanding of oceanographic processes MS Schmid, RK Cowen, K Robinson, JY Luo, C Briseño-Avena, ... Scientific Reports 10 (1), 921, 2020 | 43 | 2020 |
Three-dimensional cross-shelf zooplankton distributions off the Central Oregon Coast during anomalous oceanographic conditions C Briseño-Avena, MS Schmid, K Swieca, S Sponaugle, RD Brodeur, ... Progress in oceanography 188, 102436, 2020 | 35 | 2020 |
Changing with the tides: fine-scale larval fish prey availability and predation pressure near a tidally modulated river plume K Swieca, S Sponaugle, C Briseño-Avena, MS Schmid, RD Brodeur, ... Marine Ecology Progress Series 650, 217-238, 2020 | 23 | 2020 |
Non-carnivorous feeding in Arctic chaetognaths JJ Grigor, MS Schmid, M Caouette, VS Onge, TA Brown, RM Barthélémy Progress in oceanography 186, 102388, 2020 | 22 | 2020 |
Growth and reproduction of the chaetognaths Eukrohnia hamata and Parasagitta elegans in the Canadian Arctic Ocean: capital breeding versus income breeding JJ Grigor, MS Schmid, L Fortier Journal of Plankton Research 39 (6), 910-929, 2017 | 19 | 2017 |
Use of machine learning (ML) for predicting and analyzing ecological and ‘presence only’data: an overview of applications and a good outlook F Huettmann, EH Craig, KA Herrick, AP Baltensperger, GRW Humphries, ... Machine learning for ecology and sustainable natural resource management, 27-61, 2018 | 14 | 2018 |
The intriguing co-distribution of the copepods Calanus hyperboreus and Calanus glacialis in the subsurface chlorophyll maximum of Arctic seas MS Schmid, L Fortier Elem Sci Anth 7, 50, 2019 | 13 | 2019 |
A Convolutional Neural Network based high-throughput image classification pipeline - code and documentation to process plankton underwater imagery using local HPC … MS Schmid, D Daprano, KM Jacobson, C Sullivan, C Briseño-Avena, ... https://zenodo.org/record/4641158#.YKxHeS2ZO1s, 2021 | 12 | 2021 |
Content-aware segmentation of objects spanning a large size range: application to plankton images T Panaïotis, L Caray–Counil, B Woodward, MS Schmid, D Daprano, ... Frontiers in Marine Science 9, 870005, 2022 | 10 | 2022 |
Ensembles of ensembles: combining the predictions from multiple machine learning methods DJ Lieske, MS Schmid, M Mahoney Machine Learning for Ecology and Sustainable Natural Resource Management …, 2018 | 9 | 2018 |
9.1. Climate change and predictions of pelagic biodiversity components F Huettmann, M Schmid In: De Broyer C., Koubbi P., Griffiths H.J., Raymond B., Udekem d’Acoz C. d …, 2014 | 9 | 2014 |
A first overview of open access digital data for the Ross Sea: complexities, ethics, and management opportunities F Huettmann, MS Schmid, GRW Humphries Hydrobiologia 761, 97-119, 2015 | 7 | 2015 |
In situ imaging across ecosystems to resolve the fine‐scale oceanographic drivers of a globally significant planktonic grazer AT Greer, MS Schmid, PI Duffy, KL Robinson, MA Genung, JY Luo, ... Limnology and Oceanography 68 (1), 192-207, 2023 | 6 | 2023 |
The effect of particle properties on the depth profile of buoyant plastics in the ocean Sci M Kooi, J Reisser, B Slat, FF Ferrari, MS Schmid, S Cunsolo, R Brambini, ... Rep 6, 1-10, 2016 | 6 | 2016 |
Variational benchmarks for quantum many-body problems (2023) D Wu, R Rossi, F Vicentini, N Astrakhantsev, F Becca, X Cao, ... arXiv preprint arXiv:2302.04919, 0 | 5 | |
Edge computing at sea: High-throughput classification of in-situ plankton imagery for adaptive sampling MS Schmid, D Daprano, MM Damle, CM Sullivan, S Sponaugle, C Cousin, ... Frontiers in Marine Science 10, 1187771, 2023 | 4 | 2023 |