6 papers
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…
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…
Pairwise Matching of Intermediate Representations for Fine-grained Explainability
Lauren Shrack, Timm Haucke, Antoine Salaün +2
The differences between images belonging to fine-grained categories are often subtle and highly localized, and existing explainability techniques for deep learning models are often…
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…
DataS^3: Dataset Subset Selection for Specialization
Neha Hulkund, Alaa Maalouf, Levi Cai +15
In many real-world machine learning (ML) applications (e.g. detecting broken bones in x-ray images, detecting species in camera traps), in practice models need to perform well on s…
Counting Fish with Temporal Representations of Sonar Video
Kai Van Brunt, Justin Kay, Timm Haucke +3
Accurate estimates of salmon escapement - the number of fish migrating upstream to spawn - are key data for conservation and fishery management. Existing methods for salmon countin…