3 papers
cs.CV2026
Computer vision-based estimation of invertebrate biomass
Mikko Impiö, Philipp M. Rehsen, Jarrett Blair +5
The ability to estimate invertebrate biomass using only images could help scaling up quantitative biodiversity monitoring efforts. Computer vision-based methods have the potential…
cs.CV2025
Bridging Domain Gaps for Fine-Grained Moth Classification Through Expert-Informed Adaptation and Foundation Model Priors
Ross J Gardiner, Guillaume Mougeot, Sareh Rowlands +3
Labelling images of Lepidoptera (moths) from automated camera systems is vital for understanding insect declines. However, accurate species identification is challenging due to dom…
cs.CV2024
Insect Identification in the Wild: The AMI Dataset
Aditya Jain, Fagner Cunha, Michael James Bunsen +25
Insects represent half of all global biodiversity, yet many of the world's insects are disappearing, with severe implications for ecosystems and agriculture. Despite this crisis, d…