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Edge AI system DefoliationCAM assesses grapevine pest damage in real-time

Researchers have developed DefoliationCAM (D-CAM), an edge AI system designed to assess insect defoliation severity in grapevines in real-time. The system utilizes a YOLOX-Nano model for cordon localization and a lightweight MobileNet classifier to categorize damage levels from field-collected images. D-CAM aggregates patch predictions into a Non-linear Global Defoliation Severity (NGDS) score, which was validated against expert ratings and aligns with established thresholds for pest management. Deployed autonomously and powered by solar energy, the system demonstrated feasibility for remote monitoring and timely pest-management decisions. AI

IMPACT Enables more precise and timely pest management in agriculture through automated visual inspection.

RANK_REASON The item describes a new system and methodology published in an arXiv preprint. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Edge AI system DefoliationCAM assesses grapevine pest damage in real-time

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The item describes a new system and methodology published in an arXiv preprint. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Fuchen Li, Wei-Zhen Liang, Pin-Chu Lai, Xin Qiao, Jingqiu Chen, Haw Yen, Zonglin Yanga, Chi-En Chiang, Rudolph Avalos, Abbigail L. Rath ·

    DefoliationCAM: An Edge-AI System for Real-Time Insect Defoliation Severity Assessment in Grapevines

    arXiv:2610.20879v1 Announce Type: new Abstract: Insect-induced defoliation threatens grapevine health and yield, yet severity assessment relies on subjective manual scouting. We developed DefoliationCAM (D-CAM), a solar-powered edge AI system that estimates canopy defoliation and…