DFG-DETR: a real-time directional-aware and fine-grained detector for industrial defect detection

CF-YOLO: Context-Aware Feature Refinement for Camouflaged Industrial Micro-Defect Detection

A novel real-time detection framework designed for efficient context perception and feature refinement, bridging the gap between contextual understanding and detailed feature analysis for high-precision industrial inspection.

GDRF-DETR: real-time transmission line defect detection based on 4D anchor dynamic update and multi-scale feature refinement

MC-DETR: a lightweight RT-DETR method for industrial defect detection

Industrial defect detection requires accurate localization of small and irregular defects under complex backgrounds while maintaining low computational cost for deployment-oriented applications. To address the redundancy and limited small-defect representation of RT-DETR in industrial scenarios, this paper proposes MC-...

Dual-path attention with adaptive energy-guided interaction for real-time industrial defect detection

Detecting industrial defects presents formidable challenges, as anomalies often appear as tiny, low-contrast objects on complex surfaces with varied orientations. This work introduces two lightweight attention modules that strengthen feature discrimination while incurring minimal computational overhead. Our lightweight...

KDSP-DEA-YOLO: Knowledge-Distillation-Guided Structured Pruning for Lightweight Industrial Surface Defect Detection

Small surface defects on industrial components are characterized by small scale, low contrast, weak texture, and strong background interference. To improve deployment efficiency while preserving detection accuracy, this study proposes KDSP-DEA-YOLO based on the DEA-YOLOv8n teacher model. A heterogeneous lightweight stu...

APM-DETR: adaptive perceptual multi-scale DETR for road defect detection in complex scenes

This study proposes an adaptive perceptual multi-scale detection transformer (APM-DETR), a detection network customized for real-world complex road environments that achieves highly competitive detection accuracy, outperforming existing models on multiple defect types.