Advanced Plant Disease Segmentation in Precision Agriculture Using Optimal Dimensionality Reduction With Fuzzy C-Means Clustering and Deep Learning

Analysis of hyperspectral imagery is a critical aspect of remote sensing in precision agriculture, for which effective dimensionality reduction (DR) strategies for the inherent complexity and uncertainty of the data are highly necessary. The fusion of fuzzy logic with DR techniques offers potential...

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Vydáno v:	IEEE journal of selected topics in applied earth observations and remote sensing Ročník 17; s. 18264 - 18277
Hlavní autoři:	Bhatti, Mughair, Zeeshan, Zeeshan, MS, Syam, Bhatti, Uzair, Khan, Asad, Ghadi, Yazeed Yasin, Alsenan, Shrooq, Li, Yang, Asif, Muhammad, Afzal, Tahreem
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Accuracy Agriculture Algorithms Artificial neural networks Classification Clustering Data analysis Deep learning Feature extraction Fuzzy C-means (FCM) feature fusion Fuzzy logic graph attention network (GAT) hyperspectral image (HSI) Hyperspectral imaging Image processing Image segmentation Machine learning Neural networks Plant diseases Precision agriculture precision agriculture imaging Principal component analysis Principal components analysis Remote sensing Spatial discrimination learning Support vector machines
ISSN:	1939-1404, 2151-1535
On-line přístup:	Získat plný text
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