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PDSE-Lite:基于卷积自编码器和几次射击学习的植物疾病严重程度估计的轻量级框架

Punam Bedi1, Pushkar Gole1, Sudeep Marwaha2

  • 1Department of Computer Science, University of Delhi, New Delhi, India.

Frontiers in plant science
|January 23, 2024
PubMed
概括

一个新的框架,PDSE-Lite,使用卷积自编码器 (CAE) 和少数镜头学习 (FSL) 进行植物疾病的早期诊断和严重程度估计. 这种方法显著减少了对大量手动数据注释的需求,提供了更有效的解决方案.

关键词:
农业中的人工智能卷积式自动编码器 卷积式自动编码器植物疾病严重程度的自动估计.深度学习是一种深度学习.几次射击的学习学习

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