Emerging topics and challenges of learning from noisy data in nonstandard classification: a survey beyond binary class noise
SMOTE–IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering
Evaluating the classifier behavior with noisy data considering performance and robustness: The Equalized Loss of Accuracy measure
Multi-Granular and Multi-Criteria Large-Scale Group Decision-Making Method Using the Aggressive Ordered Aggregation Operator Created Using Sentiment Analysis
REVEL Framework to Measure Local Linear Explanations for Black‐Box Models: Deep Learning Image Classification Case Study
A tutorial on the segmentation of metallographic images: Taxonomy, new MetalDAM dataset, deep learning-based ensemble model, experimental analysis and challenges
