Computer Vision with Deep Learning for Plant Phenotyping in Agriculture: A Survey

Abstract

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.

Plant phenotyping relevance

植物フェノタイピングにおけるコンピュータビジョンと深層学習を対象とするレビューであり、方法論の整理が中心です。

Code and data availability

This is a survey article; all datasets, models, and figures mentioned (e.g., CropDeep, PlantVillage, ARIGAN) belong to cited prior works, not to this paper's own measurements or analysis. No author code, data, or asset availability statements appear, and no allowed URLs are provided.

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