705 citations
- Commonwealth Scientific and Industrial Research OrganisationAU25 papers
- UNSW SydneyAU24 papers
- Center for Astrophysics Harvard & SmithsonianUS16 papers
- Centre National de la Recherche ScientifiqueFR14 papers
- Australia Telescope National FacilityAU13 papers
- The University of SydneyAU13 papers
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Showing 2019 · cs.CVShow all
3 papers · 2 filters
cs.CV2019
Data-Efficient Classification of Birdcall Through Convolutional Neural Networks Transfer Learning
Dina B. Efremova, Mangalam Sankupellay, Dmitry A. Konovalov
Deep learning Convolutional Neural Network (CNN) models are powerful classification models but require a large amount of training data. In niche domains such as bird acoustics, it…
cs.CV2019★ 8 cited
In Situ Cane Toad Recognition
Dmitry A. Konovalov, Simindokht Jahangard, Lin Schwarzkopf
Cane toads are invasive, toxic to native predators, compete with native insectivores, and have a devastating impact on Australian ecosystems, prompting the Australian government to…
cs.CV2019★ 37 cited
Underwater Fish Detection with Weak Multi-Domain Supervision
Dmitry A. Konovalov, Alzayat Saleh, Michael Bradley +3
Given a sufficiently large training dataset, it is relatively easy to train a modern convolution neural network (CNN) as a required image classifier. However, for the task of fish…