30 citations · 76 across the 10 of their papers we have counts for
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cs.LG2026
Targeted Review for AI-Assisted Biodiversity Surveys: Active Continuous-Score Occupancy Modeling
Timm Haucke, Lauren Harrell, Justin Kay +2
We increasingly use machine learning to label scientific datasets. The models we develop and deploy are improving all the time, but they are not and will likely never be perfect. M…
q-bio.PE2026
Centering Ecological Goals in Automated Identification of Individual Animals
Lukas Picek, Timm Haucke, Lukáš Adam +16
Recognizing individual animals over time is central to many ecological and conservation questions, including estimating abundance, survival, movement, and social structure. Recent…
cs.CV2026
Deep in the Jungle: Towards Automating Chimpanzee Population Estimation
Tom Raynes, Otto Brookes, Timm Haucke +6
The estimation of abundance and density in unmarked populations of great apes relies on statistical frameworks that require animal-to-camera distance measurements. In practice, acq…