Hierarchical YOLO26 with Axis-Wise Context Block and Poincaré Supervision for Fine-Grained Ship Detection in Remote Sensing
Sensors, cilt.26, sa.20, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 26 Sayı: 20
- Basım Tarihi: 2026
- Doi Numarası: 10.3390/s26206584
- Dergi Adı: Sensors
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, EMBASE, INSPEC, MEDLINE, Directory of Open Access Journals, Academic Search Ultimate (EBSCO), Biomedical Reference Collection: Corporate Edition (EBSCO), Health Research Premium Collection (ProQuest)
- Anahtar Kelimeler: axis-wise context block, hierarchical ship recognition, oriented object detection, Poincaré supervision, remote sensing, YOLO26
- Kocaeli Üniversitesi Adresli: Evet
Özet
Fine-grained oriented ship detection remains challenging because visually similar vessel categories may exhibit substantial variations in scale, aspect ratio, and orientation. To address these challenges, this study proposes YOLO26-OBB-HMS (Hierarchical Multi-Label Supervision), a hierarchy-aware extension of YOLO26-OBB that integrates a pre-pyramid Axis-wise Context Block, local-window Feature Guidance, assignment-aligned parent-level supervision, and training-time Poincaré path learning while preserving the detector’s native oriented-box formulation and leaf-level inference scoring. Under the common class-wise AP50 evaluation protocol, the proposed n- and s-scale variants achieved 77.5% and 82.7% on the filtered HRSC2016 test partition and 75.4% and 80.6% on the prepared ShipRSImageNet final-evaluation partition, respectively.