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Updated: Feb 14, 2026

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半監視運転者の注意をそらす検出のための変形可能なピラミッド・スパース・トランスフォーマー

Qiang Zhao1, Zhichao Yu2, Jiahui Yu2

  • 1School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China.

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

この研究では,ドライバーの注意散漫を検知するための適応的な半監督のフレームワークを導入し,正確なパフォーマンスを確保するために,限られたラベル付きデータとラベルのないサンプルを使用して,安全システムを大幅に改善します.

キーワード:
YOLOベースの検出形状が変形する特徴は,核融合です.ドライバーの注意をそらすこと 検知 ドライバーの注意をそらすことドライバーモニタリングシステムインテリジェント・トランスポートシステムマルチスケール機能アラインメントオブジェクト検出 オブジェクト検出半監督学習 (semi-supervised learning) とは,半監督学習 (semi-supervised learning) とは,半監督学習 (semi-supervised learning) とは,半監督学習 (semi-supervised learning) とは,半監督学習 (semi-supervised learning) とは,半監督学習 (semi-supervised learning) とは,半監督学習 (semi-supervised learning) とは,半監督学習 (semi-supervised learning) とは,半監督学習 (semi-supervised learning) とは,半監督学習 (semi-supervised learning) とは,半監督学習 (semi-supervised learning) とは,教師・生徒のフレームワーク

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