Turnitin
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Self-taught multi-view spectral clustering
By integrating multiple views, ie, multi-view learning (ML), we can discover the underlying
data structures so that the performance of learning tasks can improve. As a basic and …
data structures so that the performance of learning tasks can improve. As a basic and …
Feature-weight and cluster-weight learning in fuzzy c-means method for semi-supervised clustering
Semi-supervised clustering aims to guide the clustering by utilizing auxiliary information
about the class labels. Among the semi-supervised clustering categories, the constraint …
about the class labels. Among the semi-supervised clustering categories, the constraint …
Robust deep fuzzy K-means clustering for image data
X Wu, YF Yu, L Chen, W Ding, Y Wang - Pattern Recognition, 2024 - Elsevier
Image clustering is a difficult task with important application value in computer vision. The
key to this task is the quality of images features. Most of current clustering methods …
key to this task is the quality of images features. Most of current clustering methods …
Efficient kernel fuzzy clustering via random Fourier superpixel and graph prior for color image segmentation
L Chen, YP Zhao, C Zhang - Engineering Applications of Artificial …, 2022 - Elsevier
The kernel fuzzy clustering algorithms can explore the non-linear relations of pixels in an
image. However, most of kernel-based methods are computationally expensive for color …
image. However, most of kernel-based methods are computationally expensive for color …