Computer Vision with Deep Learning for Plant Phenotyping in Agriculture: A Survey
It provides a comprehensive overview for researchers and practitioners in agriculture, but is incremental as it surveys existing work rather than introducing new methods.
This survey addresses the need for efficient crop management by reviewing deep learning techniques for plant phenotyping in agriculture, highlighting advancements that enable previously difficult tasks.
In light of growing challenges in agriculture with ever growing food demand across the world, efficient crop management techniques are necessary to increase crop yield. Precision agriculture techniques allow the stakeholders to make effective and customized crop management decisions based on data gathered from monitoring crop environments. Plant phenotyping techniques play a major role in accurate crop monitoring. Advancements in deep learning have made previously difficult phenotyping tasks possible. This survey aims to introduce the reader to the state of the art research in deep plant phenotyping.