Author

B. G. Weinstein

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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Ecology· 4

Signature Assays, Organisms & Methods

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Assay:imaging· 3 Research Focus:benchmarking· 2 Approach:deep learning· 2 Research Focus:ecology & biodiversity· 2 Approach:machine learning (classical)· 1 Organism:plant (other)· 1 Assay:proteomics· 1 Approach:statistical model· 1

Frequent Co-Authors

E. P. White· 4 shared A. Singh· 3 shared S. A. Bohlman· 3 shared S. Marconi· 3 shared A. Steinkraus· 2 shared A. Zare· 2 shared D. Stewart· 2 shared I. Harmon· 2 shared

Activity by Year

2021-2021 · peak 4/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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4 shared papersEcology

E. P. White

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Author profile →

4 papers

Recent·Most cited

Continental-scale hyperspectral tree species classification in the United States National Ecological Observatory Network

S. Marconi, B. G. Weinstein, S. Zou, S. A. Bohlman, A. Zare, A. Singh, D. Stewart, I. Harmon, A. Steinkraus, E. P. White

The paper develops a continental-scale tree species classifier using NEON data, showing better accuracy than site-specific models and highlighting challenges in species classification across diverse ecosystems.

bioRxiv · Dec 22, 2021Ecology

Data science competition for cross-site delineation and classification of individual trees from airborne remote sensing data

S. J. Graves, S. Marconi, D. Stewart, I. Harmon, B. G. Weinstein, Y. Kanazawa, V. M. Scholl, M. B. Joseph, J. McClinchy, L. Browne, M. K. Sullivan, S. Estrada-Villegas, E. Tusa, D. Z. Wang, A. Singh, , E. P. White

This paper runs a data science competition to improve methods for delineating and classifying individual trees from remote sensing data across multiple sites.

bioRxiv · Aug 6, 2021 · PreprintEcology

A general deep learning model for bird detection in high resolution airborne imagery

B. G. Weinstein, L. Gardner, V. Saccomanno, A. Steinkraus, A. Ortega, K. Brush, G. Yenni, A. E. McKellar, R. Converse, C. Lippitt, A. Wegmann, N. D. Holmes, A. J. Edney, T. Hart, M. J. Jessopp, , S. K. M. Ernest

The paper develops a general deep learning model for bird detection in aerial imagery, achieving high recall and precision with minimal local training.

bioRxiv · Aug 5, 2021Ecology

Disentangling the roles of inter and intraspecific variation on leaf trait distributions across the eastern United States

S. Marconi, B. G. Weinstein, J. W. Lichstein, S. A. Bohlman, A. Singh, E. P. White

The paper develops a joint model to analyze how inter- and intraspecific variation influence leaf trait distributions across the eastern US, finding that intraspecific variation significantly contributes to trait variation.

bioRxiv · Apr 1, 2021 · PreprintEcology