4 papers
Overhead Wildlife Locator (OWL): Benchmarking Weakly Supervised Learning for Aerial Wildlife Surveys
Isai Daniel Chacón, Zhongqi Miao, Bruno Demuro +9
Automated aerial wildlife surveys increasingly rely on deep learning, yet standard object detectors require bounding-box annotations, reported to be up to seven times slower and th…
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…
Multispecies Animal Re-ID Using a Large Community-Curated Dataset
Lasha Otarashvili, Tamilselvan Subramanian, Jason Holmberg +2
Recent work has established the ecological importance of developing algorithms for identifying animals individually from images. Typically, a separate algorithm is trained for each…
Understanding the Impact of Training Set Size on Animal Re-identification
Aleksandr Algasov, Ekaterina Nepovinnykh, Tuomas Eerola +4
Recent advancements in the automatic re-identification of animal individuals from images have opened up new possibilities for studying wildlife through camera traps and citizen sci…