Metaheuristic driven framework for classifying cervical cancer on smear images using deep learning approach

Computer Science

• Neural Network Model 100%
• Metaheuristics 100%
• Driven Framework 100%
• Learning Approach 100%
• Deep Learning Method 100%
• Open Source 50%
• Deep Convolutional Neural Networks 50%
• Detection Rate 50%
• Transfer Learning 50%
• Convolutional Neural Network 50%
• Class Classification 50%
• Deep Learning Model 50%
• Classification Accuracy 50%
• Segmentation Technique 50%
• Computational Time 50%
• Training Data 50%
• Pre-Trained Model 50%

INIS

• cancer 100%
• learning 100%
• images 100%
• classification 60%
• accuracy 40%
• neural networks 40%
• datasets 40%
• vision 20%
• women 20%
• patients 20%
• comparative evaluations 20%
• malignancies 20%
• data 20%
• investigations 20%
• carcinomas 20%
• sensitivity 20%
• mortality 20%
• specificity 20%
• detection 20%
• testing 20%
• economics 20%
• processing 20%

Engineering

• Learning Approach 100%
• Network Model 100%
• Deep Learning Method 100%
• Convolutional Neural Network 100%
• Computational Time 50%
• Classification Accuracy 50%
• Conventional Technique 50%
• Segmentation Technique 50%
• Transfer Learning 50%
• Survival Rate 50%