Author

D. Lehmann

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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Approach:experimental assay· 2 Assay:imaging· 2 Approach:deep learning· 1 Research Focus:ecology & biodiversity· 1 Research Focus:host-pathogen & immune response· 1 Organism:multiple species· 1

Frequent Co-Authors

A. F. Koumba Pambo· 2 shared A. W. Cardoso· 2 shared C. Orbell· 2 shared J. A. Zwerts· 2 shared J. Swiezewski· 2 shared K. A. Abernethy· 2 shared L. Bahaa-el-din· 2 shared L. Makaga· 2 shared

Activity by Year

2020-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersEcology

A. F. Koumba Pambo

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Author profile →

3 papers

Recent·Most cited

Invasion of forested areas in Gabon (Central Africa) by the Asian tiger mosquito and the potential consequences from the One Health perspective

J. Obame-Nkoghe, D. Roiz, M.-F. Ngangue, C. Costantini, N. Rahola, D. Jiolle, D. Lehmann, L. Makaga, D. Ayala, P. Kengne, C. Paupy

The paper tracks the spread of the Asian tiger mosquito in Gabon's rainforest and finds it thrives at human-forest interfaces, potentially facilitating zoonotic disease transmission.

bioRxiv · Aug 23, 2022 · PreprintEcology

Real-time alerts from AI-enabled camera traps using the Iridium satellite network: a case-study in Gabon, Central Africa

R. C. Whytock, T. Suijten, T. van Deursen, J. Swiezewski, H. Mermiaghe, N. Madamba, N. Moukoumou, J. A. Zwerts, A. F. Koumba Pambo, L. Bahaa-el-din, S. Brittain, A. W. Cardoso, P. Henschel, D. Lehmann, B. R. Momboua, , K. A. Abernethy

This paper presents a camera trap system with AI that sends real-time alerts via satellite, tested in Gabon and Europe, showing reliable operation and quick alert delivery.

bioRxiv · Nov 10, 2021Ecology

High performance machine learning models can fully automate labeling of camera trap images for ecological analyses

R. C. Whytock, J. Swiezewski, J. A. Zwerts, T. Bara-Słupski, A. F. Koumba Pambo, M. Rogala, L. Bahaa-el-din, K. Boekee, S. Brittain, A. W. Cardoso, P. Henschel, D. Lehmann, B. Momboua, C. K. Opepa, C. Orbell, , K. A. Abernethy

This paper develops a high performance machine learning model that fully automates camera trap image labeling for ecological analysis, achieving results comparable to expert labels in species richness, activity patterns, and occupancy.

bioRxiv · Sep 12, 2020 · PreprintEcology