Unsupervised Segmentation for Microstructure Identification of High Strength Steel with Superpixel Segmentation and Texture Feature Clustering
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-41341-4_54
Reference5 articles.
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2. Haralick, R., Shanmugam, K., Dinstein, I.: Textural features for image classification. Stud. Media Commun. SMC-3(6): 610–621 (1973)
3. Zhu, B., Chen, Z., Fangkang, Hu., Dai, X., Wang, L., Zhang, Y.: Feature extraction and microstructural classification of hot stamping ultra-high strength steel by machine learning. JOM 74(9), 3466–3477 (2022). https://doi.org/10.1007/s11837-022-05265-5
4. Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P., Süsstrunk, S.: SLIC Superpixels Compared to State-of-the-Art Superpixel Methods. IEEE Trans. Pattern Anal. Mach. Intell. 34(11), 2274–2282 (2012)
5. Otsu, N.: A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. 9(1): 62–66 (2007)
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