9 papers
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…
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…
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…
Application-Driven Innovation in Machine Learning
David Rolnick, Alan Aspuru-Guzik, Sara Beery +8
In this position paper, we argue that application-driven research has been systemically under-valued in the machine learning community. As applications of machine learning prolifer…
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…
Consensus-Driven Active Model Selection
Justin Kay, Grant Van Horn, Subhransu Maji +2
The widespread availability of off-the-shelf machine learning models poses a challenge: which model, of the many available candidates, should be chosen for a given data analysis ta…