Accuracy and processing speed trade-offs in classical and quantum SVM classifier exploiting PRISMA hyperspectral imagery
Author:
Affiliation:
1. Department of Astronautical, Electrical and Energy Engineering, University of Rome ‘La Sapienza’, Rome, Italy
2. Department of Civil Engineering, SRM Institute of Science and Technology, Chengalpattu, India
Publisher
Informa UK Limited
Subject
General Earth and Planetary Sciences
Link
https://www.tandfonline.com/doi/pdf/10.1080/01431161.2022.2061877
Reference65 articles.
1. Using Machine Learning for Quantum Annealing Accuracy Prediction
2. Read the fine print
3. Statistical Classification for Assessing PRISMA Hyperspectral Potential for Agricultural Land Use
4. Feature Selection and Classification of Hyperspectral Images With Support Vector Machines
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