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Updated: Sep 9, 2025

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GhostConv+CA-YOLOv8n:リアルな複雑な背景の低レベルの特徴を集約した,米の害虫検出のための軽量なネットワーク

Fei Li1, Yang Lu1, Qiang Ma1

  • 1College of Information and Electrical Engineering, Heilongjiang Bayi Agricultural University, Daqing, China.

Frontiers in plant science
|August 29, 2025
PubMed
まとめ

この研究は,効率的な米の害虫検出のための軽量なディープラーニングモデル,GhostConv+CA-YOLOv8nを紹介しています. 複雑なフィールド条件で高い精度とリコールを達成し,既存の方法の限界に対処します.

キーワード:
ゴーストコンブシェイプ・ロウスライド 損失文脈集積ブロック米の害虫検出

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