Journal of Applied Optics, Volume. 45, Issue 4, 759(2024)
Image segmentation method for metal coating peeling and corrosion based on improved U2-Net network
[1] HARSIMRAN S, SANTOSH K, RAKESH K. Overview of corrosion and its control: a critical review[J]. Progress in Engineering Science, 3, 13-24(2021).
[2] VOEOBEL R, IVASENKO I, BEREHULYAK O et al. Segmentation of rust defects on painted steel surfaces by intelligent image analysis[J]. Automation in Construction, 123, 103515(2021).
[3] YANG Jihua, YANG Hua, JIA Weiding et al. Adaptive enhancement method for LiDAR images based on multiscale retinex[J]. Laser Journal, 44, 192-197(2023).
[5] HUANG Z, WANG X, HUANG L et al. Ccnet: criss-cross attention for semantic segmentation[C], 603-612(2019).
[7] CHOLLET F. Xception: deep learning with depthwise separable convolutions[C], 1251-1258(2017).
[8] TAN M, LE Q. Efficientnet: rethinking model scaling for convolutional neural networks[C], 6105-6114(2019).
[9] WU Y, SHEN X, BU F et al. Ultrasound image segmentation method for thyroid nodules using ASPP fusion features[J]. IEEE Access, 8, 172457-172466(2020).
[10] CHEN L C, PAPANDREOU G, KOKKINOS I et al. Deeplab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40, 834-848(2017).
[13] WOO S, PARK J, LEE J Y et al. Cbam: convolutional block attention module[J]. Proceedings of the European Conference on Computer Vision, 11211, 3-19(2018).
[14] LI Cuiyun, BAI Jing, ZHENG Liang. Medical image segmentation based on the fusion of edge enhancement attention mechanism and U-Net network[J]. Journal of Graphics, 43, 273-278(2022).
[15] QIN X, ZHANG Z, HUANG C et al. U2-Net: going deeper with nested U-structure for salient object detection[J]. Pattern Recognition, 106, 107404(2020).
[16] RONNEBERGER O, FISCHER P, BROX T. U-net: convolutional networks for biomedical image segmentation[C], 234-241(2015).
[17] LIU S, HUANG D. Receptive field block net for accurate and fast object detection[C], 385-400(2018).
[19] SZEGEDY C, VANHOUCKE V, IOFFE S et al. Rethinking the inception architecture for computer vision[C], 2818-2826(2016).
[20] LIN T Y, GOYAL P, GIRSHICK R et al. Focal loss for dense object detection[C], 2980-2988(2017).
[21] SALEHI S M, ERDOGMUS D, GHOLIPOUR A. Tversky loss function for image segmentation using 3D fully convolutional deep networks[C], 379-387(2017).
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Yunfeng NI, Qingting QI, Daixian ZHU, Qiang QIU, Shulin LIU. Image segmentation method for metal coating peeling and corrosion based on improved U2-Net network[J]. Journal of Applied Optics, 2024, 45(4): 759
Category: Research Articles
Received: Jun. 21, 2023
Accepted: --
Published Online: Oct. 21, 2024
The Author Email: Daixian ZHU (朱代先)