التفاصيل البيبلوغرافية
| العنوان: |
Oil palm diseases detection using computer vision techniques. |
| المؤلفون: |
Yang, Soh Yi, Ling, Lew Sook, Yin, Ooi Shih |
| المصدر: |
AIP Conference Proceedings; 2024, Vol. 3153 Issue 1, p1-7, 7p |
| مصطلحات موضوعية: |
MULTISPECTRAL imaging, OIL palm, COMPUTER vision, DEEP learning, NORMALIZED difference vegetation index, MACHINE learning, DRONE aircraft |
| مصطلحات جغرافية: |
MALACCA (Malacca, Malaysia), SABAH |
| مستخلص: |
Unmanned aerial vehicles (UAVs), with sensors that can detect spectrums are useful tools for spotting diseases early in crops. This research zooms in on identifying Ganoderma disease in oil palm farms in Melaka and Sabah using UAV images. This research analyzed RGB pictures taken by the UAV mounted camera and multispectral data boosting their precision with georeferencing techniques. By employing the Normalized Green-Red Difference Index (NGRDI) and Normalized Difference Vegetation Index (NDVI) for image examination we effectively outlined the boundaries of oil palm trees. Future research should explore deep learning algorithms and further exploit NDVI to enhance disease detection. These developments are vital for improving strategies to detect and manage Ganoderma disease in oil palm plantations. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
