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Automatic Plant Cover Estimation with Convolutional Neural Networks
2021
Monitoring the responses of plants to environmental changes is essential for plant biodiversity research. This, however, is currently still being done manually by botanists in the field. This work is very laborious, and the data obtained is, though following a standardized method to estimate plant coverage, usually subjective and has a coarse temporal resolution. To remedy these caveats, we investigate approaches using convolutional neural networks (CNNs) to automatically extract the relevant
doi:10.18420/informatik2021-039
fatcat:nwwlj5n5bjgpbdwtlcup23x6vu