Detecting abnormal human behaviors in surveillance videos is crucial for various domains,
including security and public safety. Many successful detection techniques based on deep …

Pavement management systems play a vital role in maintaining transportation infrastructures
by evaluating pavement distress to perform maintenance tasks efficiently. Severity analysis …

Clustering is a process widely studied in the field of pattern recognition. Despite the
existence of numerous algorithms and continuous innovation, there are still unresolved …

The possibilistic c-means clustering (PCM) algorithm improves the robustness of fuzzy c-
means clustering (FCM) to noise and outliers by releasing the probabilistic constraint of …

Controlling the impact of partial supervision on the outcomes of modeling is of uttermost
importance in semi-supervised fuzzy clustering. Semi-Supervised Fuzzy C-Means …

Traditional clustering algorithms always suffer from tough issues in the clustering of complex
multi-dimensional data with multiple characteristics, such as significantly imbalanced sizes …

Possibilistic fuzzy c-means is a widely used fuzzy clustering algorithm. This algorithm is
capable of handling outlier data points, rendering it a viable option for maintaining a data …

This study proposes a hybrid multi-objective meta-heuristics and possibilistic intuitionistic
fuzzy c-means (PIFCM) algorithms for cluster analysis. The PIFCM algorithms combine …

Safe semi-supervised clustering (S3C) has recently made remarkable progress in the
machine learning field and numerous S3C methods have been proposed to estimate safe …

The improved fuzzy c-means (IFCM) algorithm is an effective technique for handling the
“uniform effect” in imbalanced data clustering; it adjusts the weight of each class based on …