Image segmentation by generalized hierarchical fuzzy C-means algorithm

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Firefly algorithm with neighborhood attraction (2017, methodology): “To implement image segmentation [27, 49], Hassanzadeh et al.”
Research on denoising sparse autoencoder (2016, methodology): “Apart from that autoencoder can also be used in image segmentation [17], cluster [18] and classiﬁcation [19, 20].”
Mapping of Urban Surface Water Bodies from Sentinel-2 MSI Imagery at 10 m Resolution via NDWI-Based Image Sharpening (2017, background): “The use of an empirically selected threshold (normally zero) can overestimate or underestimate water area because threshold values vary among regions depending on different image characteristics [30,31].”
MultiResUNet : Rethinking the U-Net Architecture for Multimodal Biomedical Image Segmentation (2019, methodology): “Consequently, more adaptive algorithms were developed relying on geometric shape priors with tools of soft-computing [8] and fuzzy algorithms [9].”
A new narrow band vegetation index for characterizing the degree of vegetation stress due to copper: the copper stress vegetation index (CSVI) (2017, methodology): “In addition, robustness is important for the applicability of a method (Zhou et al. 2016; Yuhui et al. 2015).”