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20242026
most citedApplication-Driven Innovation in Machine Learning

3 citations · 4 across the 4 of their papers we have counts for

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9 papers · 1 filter

cs.CV2026

Teach a Molmo2Fish: Towards interactive fish tracking with natural language guidance

Kai Van Brunt, Justin Kay, Sara Beery

Computer vision is increasingly used to automate recognition tasks in large ecological datasets, but more complex tasks such as multi-object tracking continue to pose challenges. A…

cs.CV2026

When One Modality Is Not Enough: Multimodal Sex and Life-Stage Classification of Red Deer from Aerial RGB-Thermal Video

Hugo Markoff, Christoph Praschl, Ivan Ludoški +3

Aerial drone surveys increasingly support wildlife population estimation, yet a useful census is more than a count: population dynamics are defined by species composition, sex rati…

cs.CV2026

Oh Deer, How Should I Handle This? Seasonal Priors for Selective Wildlife Annotation and Classification

Hugo Markoff, Christoph Praschl, Anton Hjalte Jørgensen +7

Fine-grained wildlife classification in aerial imagery is limited not only by model performance, but also by unreliable labels: animals occupy few pixels, key visual cues vary seas…

cs.CV20251 cited

Open-Insect: Benchmarking Open-Set Recognition of Novel Species in Biodiversity Monitoring

Yuyan Chen, Nico Lang, B. Christian Schmidt +5

Global biodiversity is declining at an unprecedented rate, yet little information is known about most species and how their populations are changing. Indeed, some 90% of Earth's sp…

cs.CV2025

Align and Distill: Unifying and Improving Domain Adaptive Object Detection

Justin Kay, Timm Haucke, Suzanne Stathatos +5

Object detectors often perform poorly on data that differs from their training set. Domain adaptive object detection (DAOD) methods have recently demonstrated strong results on add…

cs.CV2025

Visually Consistent Hierarchical Image Classification

Seulki Park, Youren Zhang, Stella X. Yu +2

Hierarchical classification predicts labels across multiple levels of a taxonomy, e.g., from coarse-level 'Bird' to mid-level 'Hummingbird' to fine-level 'Green hermit', allowing f…