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The aim is to develop an advanced framework for detecting small cable surface defects in power transmission systems.

May 9, 2026ElectronicsOpen Access

An Enhanced YOLO Framework for Accurate Small-Target Cable Defect Detection

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The aim is to develop an advanced framework for detecting small cable surface defects in power transmission systems.
Proposed YOLO-ESBD framework focuses on coordinated optimization across feature extraction, preservation, and prediction.
Introduced EMA for feature discrimination and SPD-Conv for preserving fine-grained spatial information.
Utilized BiFPN for multi-scale feature fusion and DyHead for adaptive detection under varying defect conditions.
YOLO-ESBD achieved an mAP@0.5 of 94.2%, outperforming baseline methods.
Real-time performance of 86.2 FPS on RK3588 under INT8 quantization.
Stable performance across various deployment platforms.

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Randomized trial demonstrates improved defect detection in industrial cables, suggesting enhanced safety protocols.

Yang et al. (2026) studied this question.

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