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Updated: Sep 10, 2025

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自動運転のためのYOLOv5の強化:エッジデバイスの効率的な注意ベースのオブジェクト検出

Mortda A A Adam1, Jules R Tapamo1

  • 1School of Engineering, Howard College Campus, University of KwaZulu-Natal, Durban 4041, South Africa.

Journal of imaging
|August 27, 2025
PubMed
まとめ

この研究は,自動運転のための軽量なオブジェクト検出モデルを導入し,注意力メカニズムでYOLOv5を強化します. BaseECAx2モデルは効率的なエッジ展開を提供し,BaseSE-ECAは重要な車両検出タスクにおいて高い精度を達成します.

キーワード:
注意力メカニズム自動運転エッジ・デバイス軽量モデルオブジェクト検出車両検出

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