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Moritz S. Schmid
Moritz S. Schmid
Research Associate, Hatfield Marine Science Center, Oregon State University
Verified email at oregonstate.edu - Homepage
Title
Cited by
Cited by
Year
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
2642016
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
532016
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
452013
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
442018
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
422020
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
342020
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
212020
Non-carnivorous feeding in Arctic chaetognaths
JJ Grigor, MS Schmid, M Caouette, VS Onge, TA Brown, RM Barthélémy
Progress in oceanography 186, 102388, 2020
212020
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
192017
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
142018
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
132019
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
122021
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
92022
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
82014
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
72015
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
62023
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
62018
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
6
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
42023
Assessments of carbon stock hotspots in Nicaragua and Costa Rica
MS Schmid, AP Baltensperger, J Grigor, F Huettmann
Central American biodiversity: Conservation, ecology, and a sustainable …, 2015
42015
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Articles 1–20