An AI-Driven Dual-Spectral Vision-Language Sensing Framework for Intelligent Agricultural Phenotyping.

Abstract excerpt

Seed varietal purity and physiological viability are critical determinants of crop yield and quality. However, non-destructive assessment faces significant challenges in fine-grained variety discrimination and the perception of internal defects. This study proposes S3-Net, an AI-driven multimodal sensing framework that integrates vision-language alignment with dual-spectral sensor fusion for autonomous seed...

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