IEEE

Efficient Multi-label Feature Selection via High-order Structure Information

Abstract: Multi-label feature selection (MFS) aims to select effective features that can be associated with multiple class labels. However, existing MFS methods usually constrain the feature selection ...
GitHub

TFM Dataset & Benchmark: Automated Tear Film Break-Up Analysis

Classification (TF-Cls) 'Clear', 'Closed', 'Broken', 'Blur' 6,247 3632 × 2760 4,687:561:999(75%:9%:16%) Object Detection (TF-Det) Inside, Middle, Outside Rings 4,736 ...
Frontiers

From scales to circuits: integrating behavioral diagnosis and neural biomarkers for improved classification in disorders of consciousness

Introduction: In this study, we propose a data-driven approach that integrates behavioral diagnosis with neuroimaging features to identify representative UWS and MCS patients from a large inpatient ...
IEEE

Dual Passive-Aggressive Stacking k-Nearest Neighbors for Class-Incremental Multi-Label Stream Classification

Abstract: Class-incremental multi-label stream classification (class-incremental MLSC) requires learning algorithms to adapt to concept drifts, perform single-pass online learning, and handle emerging ...