Fine-Tuned Residual Network-Based Features with Latent Variable Support Vector Machine-Based Optimal Scene Classification Model for Unmanned Aerial Vehicles

Computer Science

• Unmanned Aerial Vehicle 100%
• Classification Models 100%
• Support Vector Machine 100%
• Residual Neural Network 100%
• Feature Extraction 80%
• Search Algorithm 20%
• Classification Accuracy 20%
• Object Detection 20%
• Convolution Layer 20%
• Feature Vector 20%
• Open Access 20%

Engineering

• Unmanned Aerial Vehicle 100%
• Support Vector Machine 100%
• Based Feature Extraction 100%
• Deep Learning 25%
• Classification Accuracy 25%
• Feature Vector 25%
• Surveillance System 25%
• Search Algorithm 25%
• Power Line 25%
• Land Use 25%

Biochemistry, Genetics and Molecular Biology

• Support Vector Machine 100%
• Dynamics 50%
• Electric Potential 50%
• Extract 50%