関連する実験動画

Updated: Feb 14, 2026

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss
07:12

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Published on: April 11, 2025

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I-GhostNetV3: スマート・アグリカルチャーにおけるビジョン・センサ・ベース・ライス・リーフ・疾患検出のための軽量なディープ・ラーニング・フレームワーク

Puyu Zhang1, Rui Li1, Yuxuan Liu2

  • 1College of Electronic Information Engineering, Guangdong University of Petrochemical Technology, Maoming 525000, China.

Sensors (Basel, Switzerland)
|February 13, 2026
PubMed
まとめ

この研究では,コンピュータビジョンを使用して米の葉の病気を特定するための効率的なAIモデルであるI-GhostNetV3を紹介しています. 複雑なフィールド条件下でも高い精度を達成し,スマートな農業アプリケーションを支援します.

キーワード:
I-ゴーストネットV3V3注意力メカニズム 注意力メカニズム軽量なコンヴォルションネットワーク米の病気の分類スマート農業 スマート農業視力センサー 視力センサー

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