Steel Surface Defect Detection Network Combining Element-Wise Multiplication Operators and Channel Pruning

doi:10.3778/j.issn.1002-8331.2408-0017

Abstract

Abstract: To address the challenge of real-time and high-precision defect detection on resource-constrained devices, a steel surface defect detection network is proposed which combines element-wise multiplication operators with channel pruning. To enhance the ability to capture defect characteristics, a feature space expansion module (FSEM) and an edge feature extraction module are designed, and a lightweight and efficient feature extraction network (LENet) is developed using a four-layer hierarchical architecture. To improve the effective fusion of multi-scale features, an adaptive multi-scale feature fusion network (AMFN) is constructed using the adaptive fusion (AW-Fusion) module based on channel-prior convolutional attention (CPCA) and FSEM within a feature pyramid architecture. To reduce network complexity and improve detection speed, channel pruning is employed for backend compression. Related experiments are conducted on the NEU-DET dataset to validate the effectiveness and superiority of the proposed network. Experimental results indicate that the pruned network achieves an accuracy of 78.1% and a speed of 179.8 FPS under low complexity, meeting practical application requirements.

Key words: element-wise multiplication operators, steel surface, defect detection, channel pruning

摘要： 针对目前钢材表面缺陷检测网络在资源受限设备上难以实时精准检测的问题，提出了一种联合元素乘法算子与通道剪枝的钢材表面缺陷检测网络。为提高缺陷特征的有效提取，设计了特征空间膨胀模块（feature space expansion module，FSEM）和边缘特征提取模块，采用四层分层架构构建轻量级高效特征提取网络（lightweight and efficient feature extraction network，LENet）；为提升多尺度特征的有效融合，基于通道先验卷积注意力（channel-prior convolutional attention，CPCA）设计了自适应融合（adaptive fusion，AW-Fusion）模块和FSEM，采用特征金字塔架构构建自适应多尺度特征融合网络（adaptive multi-scale feature fusion network，AMFN）；为降低网络复杂度和提升网络检测速度，采用通道剪枝对网络进行后端压缩。在数据集NEU-DET上进行相关实验来验证网络的有效性和优越性。实验结果表明，剪枝后的网络在低复杂度下检测精度为78.1%，检测速度为179.8 FPS，满足实际应用需求。

关键词: 元素乘法算子, 钢材表面, 缺陷检测, 通道剪枝

YANG Chunlong, LYU Donghao, ZHANG Yong, TIAN Xu, WANG Chengzhi. Steel Surface Defect Detection Network Combining Element-Wise Multiplication Operators and Channel Pruning[J]. Computer Engineering and Applications, 2025, 61(22): 245-256.

杨春龙, 吕东澔, 张勇, 田旭, 王城智. 联合元素乘法算子与通道剪枝的钢材表面缺陷检测网络[J]. 计算机工程与应用, 2025, 61(22): 245-256.

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