Deep learning object detection to estimate the nectar sugar mass of flowering vegetation

Deep learning object detection to estimate the nectar sugar mass of flowering vegetation

Abstract Floral resources are a key driver of pollinator abundance and diversity, yet their quantification in the field and laboratory is laborious and requires specialist skills. Using a dataset of 25,000 labelled tags of fieldwork‐realistic quality, a convolutional neural network (Faster R‐CNN) wa...

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Bibliographic Details
Main Authors: Damien Hicks, Mathilde Baude, Christoph Kratz, Pierre Ouvrard, Graham Stone
Format: Article
Language:English
Published: Wiley 2021-07-01
Series:Ecological Solutions and Evidence
Subjects:
convolutional neural network
deep learning
Faster R‐CNN
nectar sugar mass
object detection
pollinator food resources
Online Access:https://doi.org/10.1002/2688-8319.12099

Internet

https://doi.org/10.1002/2688-8319.12099

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