Author

M. Locatelli

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Biophysics· 1 Ecology· 1

Signature Assays, Organisms & Methods

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Approach:Bayesian inference· 1 Research Focus:benchmarking· 1 Research Focus:cell signaling & trafficking· 1 Approach:deep learning· 1 Research Focus:ecology & biodiversity· 1 Assay:fluorescence / live-cell microscopy· 1 Approach:statistical model· 1

Frequent Co-Authors

F. Iqbal· 1 shared J. Chenal· 1 shared J. Lawrimor· 1 shared J. Liu· 1 shared K. Bloom· 1 shared K. Bonin· 1 shared M. Bosch· 1 shared M. Zhang· 1 shared

Activity by Year

2020-2020 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperBiophysics

F. Iqbal

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2 papers

Recent·Most cited

Evaluating urban greening scenarios for urban heat mitigation: a spatially-explicit approach

M. Bosch, M. Locatelli, P. Hamel, R. Jaligot, J. Chenal, S. Joost

This paper evaluates urban greening scenarios for heat mitigation using a spatially-explicit approach and the InVEST model in Lausanne.

bioRxiv · Nov 9, 2020 · PreprintEcology

Performance of deep learning restoration methods for the extraction of particle dynamics in noisy microscopy image sequences

P. Kefer, F. Iqbal, M. Locatelli, J. Lawrimor, M. Zhang, K. Bloom, K. Bonin, P.-A. Vidi, J. Liu

This study evaluates deep learning denoising methods for improving particle tracking accuracy in noisy microscopy images, finding supervised learning generally outperforms unsupervised approaches.

bioRxiv · Nov 4, 2020Biophysics