Leveraging Zero-Shot Detection Mechanisms to Accelerate Image Annotation for Machine Learning in Wild Blueberry (<i>Vaccinium angustifolium</i> Ait.)

Leveraging Zero-Shot Detection Mechanisms to Accelerate Image Annotation for Machine Learning in Wild Blueberry (<i>Vaccinium angustifolium</i> Ait.)

This study conducted an analysis of zero-shot detection capabilities using two frameworks, YOLO-World and Grounding DINO, on a selection of images in the wild blueberry (<i>Vaccinium angustifolium</i> Ait.) cropping system. The datasets included ripe wild blueberries, hair fescue (<i&...

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Bibliographic Details
Main Authors: Connor C. Mullins, Travis J. Esau, Qamar U. Zaman, Chloe L. Toombs, Patrick J. Hennessy
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Agronomy
Subjects:
precision agriculture
object detection
automated annotation
grounding DINO
YOLO-World
Online Access:https://www.mdpi.com/2073-4395/14/12/2830
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