QR kód

No more laborious stem counting: AI-powered computer vision enables identification and quantification of solid and hollow alfalfa stems at the pixel level

Traditional alfalfa stem phenotyping is labor-intensive and susceptible to bias from subjective ratings. Computer vision and machine learning present a promising solution for objectively assessing stem morphology. This study proposed an AI-driven image analysis to replace manual phenotyping methods...

Celý popis

Uloženo v:
Hlavní autoři: Brandon J. Weihs, Zhou Tang, Somshubhra Roy, Zezhong Tian, Deborah Jo Heuschele, Zhiwu Zhang, Cranos Williams, Zhou Zhang, Garett Heineck, Swayamjit Saha, Zhanyou Xu
Médium: Artigo
Jazyk:Inglês
Vydáno: Elsevier 2025-12-01
Edice:Smart Agricultural Technology
Témata:
YOLO
Computer vision
Alfalfa
Image analysis
Pixel
Stem hollowness
On-line přístup:http://www.sciencedirect.com/science/article/pii/S277237552500509X
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Podobné jednotky