Author

A. Steinkraus

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· 3

Signature Assays, Organisms & Methods

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

Frequent Co-Authors

E. P. White· 3 shared A. Ortega· 2 shared B. G. Weinstein· 2 shared H. Senyondo· 2 shared P. Frederick· 2 shared A. E. McKellar· 1 shared A. J. Edney· 1 shared A. Singh· 1 shared

Activity by Year

2021-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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3 shared papersEcology

E. P. White

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Author profile →

3 papers

Recent·Most cited

Near real-time monitoring of wading birds using uncrewed aircraft systems and computer vision

E. P. White, L. Garner, B. Weinstein, H. Senyondo, A. Ortega, A. Steinkraus, G. M. Yenni, P. Frederick, S. M. Ernest

This paper presents an end-to-end workflow for near real-time monitoring of wading birds using drones and computer vision, achieving species-level counts for five out of six target species.

bioRxiv · May 14, 2024Ecology

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

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