3 papers
cs.CV2026
MAPLE: Multi-Path Adaptive Propagation with Level-Aware Embeddings for Hierarchical Multi-Label Image Classification
Boshko Koloski, Marjan Stoimchev, Jurica LevatiÄ +2
Hierarchical multi-label classification (HMLC) is essential for modeling structured label dependencies in remote sensing. Yet existing approaches struggle in multi-path settings, w…
cs.CV2026
HELM: Hierarchical and Explicit Label Modeling with Graph Learning for Multi-Label Image Classification
Marjan Stoimchev, Boshko Koloski, Jurica LevatiÄ +2
Hierarchical multi-label classification (HMLC) is essential for modeling complex label dependencies in remote sensing. Existing methods, however, struggle with multi-path hierarchi…
cs.LG2024
Semi-supervised Predictive Clustering Trees for (Hierarchical) Multi-label Classification
Jurica LevatiÄ, Michelangelo Ceci, Dragi Kocev +1
Semi-supervised learning (SSL) is a common approach to learning predictive models using not only labeled examples, but also unlabeled examples. While SSL for the simple tasks of cl…