Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification

Keyphrases

• Aerial Image Dataset 20%
• Aerial Imagery 20%
• Aerial Scenes 20%
• Binary Pattern 100%
• Classification Benchmark 20%
• Color Information 20%
• Comprehensive Experiment 20%
• Computer Vision Problems 20%
• Convolutional Neural Network 100%
• Convolutional Neural Network Model 40%
• De-facto 20%
• Deep Learning Architectures 20%
• Deep Model 40%
• Deep Network 20%
• Early Fusion 20%
• Fusion Architecture 20%
• ImageNet 20%
• Imaging Condition 20%
• Labeled Data 20%
• Late Fusion 40%
• Local Binary Pattern 40%
• Local Features 20%
• Material Analysis 20%
• Material Recognition 20%
• Network Architecture 20%
• Network Fusion 20%
• Pattern-based 20%
• Problem Recognition 20%
• Recent Approaches 20%
• Recognition Dataset 20%
• Remote Sensing Image Classification 100%
• Satellite Imagery 20%
• Scene Categories 20%
• Scene Type 20%
• Statistical Distribution 20%
• Texture Description 20%
• Texture Features 20%
• Texture Information 40%
• Texture Recognition 100%

INIS

• applications 12%
• architecture 50%
• benchmarks 12%
• classification 100%
• color 12%
• comparative evaluations 12%
• computers 12%
• data 12%
• datasets 25%
• distribution 12%
• images 25%
• information 50%
• learning 12%
• neural networks 100%
• performance 12%
• remote sensing 100%
• satellites 12%
• texture 100%
• uranium carbides 12%
• vision 12%

Computer Science

• Color Information 20%
• Computer Vision 20%
• Convolutional Neural Network 100%
• Deep Architecture 20%
• local feature 20%
• Network Architecture 20%
• Neural Network Model 40%
• Recognition Problem 20%
• Statistical Distribution 20%
• Texture Feature 20%
• Texture Information 40%