D. Pamučar

Adaptive multi-level feature learning framework for natural disaster image classification

This work proposes a novel multi-level feature-learning framework that incorporates adaptive image enhancement, hybrid segmentation, multi-texture feature extraction, attention-based classification, and a self-adaptive optimization strategy within a single architecture for image classification of natural disasters.

Promoting responsible and energy conscious artificial intelligence: An enhanced measurement of alternatives and ranking according to compromise solution approach via disc spherical fuzzy Sugeno–Weber Z-aggregation information