A Knowledge-Enhanced Object Detection for Sustainable Agriculture

The integration of autonomous aerial vehicles (AAVs) in agriculture has advanced precision farming by enhancing the ability to monitor and optimize agricultural plots. Object detection-critical for identifying crops, pests, and diseases-presents challenges due to data availability and varying enviro...

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Veröffentlicht in:	IEEE journal of selected topics in applied earth observations and remote sensing 2025-01, Vol.18, p.728-740
Hauptverfasser:	Djenouri, Youcef, Belbachir, Ahmed Nabil, Michalak, Tomasz, Belhadi, Asma, Srivastava, Gautam
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Adaptability Adaptation models Agriculture Autonomous aerial vehicles Computational modeling Crops Data models Deep learning Environmental conditions Environmental impact Environmental management Feature extraction Image enhancement Knowledge bases (artificial intelligence) knowledge guided deep learning Mental task performance object detection Object recognition Pests Precision farming remote sensing Resource management Sustainability Sustainable agriculture Unmanned aerial vehicles Visual discrimination learning Visual system YOLO
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