A synergistic hybrid approach for calorie estimation using multi-view food images and deep learning-based segmentation and classification

Key Points

• Calorie estimation accuracy is significantly enhanced using a hybrid deep learning method.
• The model achieved a precision of 92% across various food categories and image views.
• Utilization of deep learning algorithms for the segmentation and classification of food items aids the process.
• The findings highlight the need for advanced techniques in calorie tracking methods.