An adaptive deep learning framework for dynamic image classification in the internet of things environment

Keyphrases

• Adaptive Convolutional Neural Network 40%
• CIFAR-10 20%
• Class Evaluation 20%
• Classification Accuracy 20%
• Classification Model 20%
• Clustering Methods 20%
• Collaborative Deep Learning 100%
• Concept Change 20%
• Data Perturbation 20%
• Data Sensing 20%
• Deep Learning Framework 100%
• Deep Learning Methods 20%
• Deep Learning Model 20%
• Dermatologist 20%
• Dermoscopy 20%
• Digitization 20%
• Disease Data 20%
• Dynamic Adaptive 20%
• Dynamic Image 100%
• Ensemble Framework 20%
• Euclidean Distance Measure 20%
• Future Concerns 20%
• High Dimension 20%
• Image Classification 100%
• Image Data 20%
• Intelligent Applications 20%
• Intelligent Healthcare System 20%
• Internet Connectivity 20%
• Internet of Things 20%
• Internet of Things Environment 100%
• ISIC 2019 20%
• Learning Classifiers 20%
• Modern History 20%
• Neural Network Ensemble 40%
• New Arrivals 20%
• Novel Class 60%
• Online Classifier 40%
• Online Training 40%
• Sensing Technology 20%
• Shallow Learning 20%
• Silhouette Method 20%
• Skin Diseases 20%
• Temporal Data 20%
• Temporal Inconsistency 20%

Computer Science

• Change Concept 20%
• Classification Accuracy 20%
• Classification Models 20%
• Convolutional Neural Network 40%
• Data Stream 20%
• Deep Learning 100%
• Deep Learning Model 20%
• Euclidean Distance 20%
• Image Classification 100%
• Internet Connection 20%
• Internet of Things 100%
• Issue Evolution 40%
• Learning Approach 20%
• Learning Framework 100%
• Temporal Data 20%
• Training Module 20%