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We propose H-SGE (Hybrid Scene Graph Enrichment), combining Generative Adversarial Networks (GANs), scene graph enrichment, and multiple YOLO variants (YOLOv5, YOLOv7, YOLO10, YOLO11) for enhanced detection. H-SGE employs a five-stage pipeline: (1) enriched scene graph generation, (2) GAN-based feature enhancement, (3) context-aware RoI selection, (4) multi-YOLO detection, and (5) output fusion. Evaluation on a handgun dataset demonstrates significant F1-score improvements: YOLOv5 from 58% to 80%, YOLOv7 from 56% to 82%, YOLO10 from 62% to 85%, and YOLO11 from 64% to 87%, achieving over 20% accuracy gains. Results show that combining contextual reasoning with visual augmentation and hybrid detection effectively addresses small object detection challenges in surveillance systems.<\/jats:p>","DOI":"10.1007\/s11760-025-04926-7","type":"journal-article","created":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T12:38:15Z","timestamp":1762432695000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["H-SGE: A hybrid model based on scene graph enrichment for automated Handgun detection in security surveillance"],"prefix":"10.1007","volume":"19","author":[{"given":"Nasreen","family":"Jawaid","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Najma Imtiaz","family":"Ali","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Imtiaz Ali","family":"Korejo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Imtiaz Ali","family":"Brohi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nor Hafeizah","family":"Hassan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,11,6]]},"reference":[{"key":"4926_CR1","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1016\/j.neucom.2015.09.116","volume":"187","author":"Y Guo","year":"2016","unstructured":"Guo, Y., Liu, Y., Oerlemans, A., Lao, S., Wu, S., Lew, M.: Deep learning for visual understanding: A review. 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