Bilateral guidance network for one-shot metal defect segmentation

Author:

Shan DexingORCID,Zhang YunzhouORCID,Liu XiaozhengORCID,Zhao Jiaqi,Coleman Sonya,Kerr Dermot

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference41 articles.

1. Trainable guided attention based robust leather defect detection;Aslam;Eng. Appl. Artif. Intell.,2023

2. Triplet-graph reasoning network for few-shot metal generic surface defect segmentation;Bao;IEEE Trans. Instrum. Meas.,2021

3. Bergmann, P., Fauser, M., Sattlegger, D., Steger, C., 2019. MVTec AD–A comprehensive real-world dataset for unsupervised anomaly detection. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 9592–9600.

4. A pixel-level segmentation convolutional neural network based on deep feature fusion for surface defect detection;Cao;IEEE Trans. Instrum. Meas.,2020

5. Rethinking atrous convolution for semantic image segmentation;Chen,2017

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