A Novel Curriculum Learning Training Strategy for Pomegranate Growth Stage Classification Using YOLO Models on Multi-Source Datasets for Precision Agriculture

A Novel Curriculum Learning Training Strategy for Pomegranate Growth Stage Classification Using YOLO Models on Multi-Source Datasets for Precision Agriculture

Pomegranates are among the many vital crops generally believed to offer health quality and economically impact agriculture. Accurate detection and classification of the pomegranate growth stages enables fruit harvesting robots, resulting in yield optimization, supply chain, and market readiness. In...

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Bibliographic Details
Main Authors: N. Shobha Rani, K. R. Bhavya, A. Vadivel, T. Vasudev, Raghavendra M. Devadas, Vani Hiremani
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Curriculum learning
precision agriculture
deep learning
multi-source datasets
image-based crop monitoring
Online Access:https://ieeexplore.ieee.org/document/11045383/
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