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Speeded-up Simple Linear Iterative Clustering Based on Region Homogeneity

2019 2nd International Conference on Safety Produce Informatization (IICSPI), 2019
For better analyzing and adopting superpixel methods in image segmentation, an improved Simple Linear Iterative Clustering (SLIC) algorithm is put forward, which sustains that homogeneous regions show high consistence during clustering.
Zhifei Wei   +3 more
semanticscholar   +1 more source

Enhanced K-means Color Clustering Based on SLIC Superpixels Merging incorporated within the Entomology Software: AInsectID

IEEE Conference on Evolving and Adaptive Intelligent Systems
Superpixel-based segmentation is an important pre-processing step for the simplification of image processing. The subjective nature behind the determination of optimal cluster numbers in segmentation algorithms can result in either underor over ...
Haleema Sadia, Parvez Alam
semanticscholar   +1 more source

Semi-supervised possibilistic Gustafson-Kessel clustering algorithm based on SLIC and MR

Proceedings of the 2024 7th International Conference on Artificial Intelligence and Pattern Recognition
The possibilistic c-means clustering (PCM) modifies the condition that the sum of the fuzzy memberships of each sample point is one, which improves the robustness of the fuzzy c-means algorithm (FCM) to noise and outliers.
Junnan Liu, Haiyan Yu, Yuting Wu
semanticscholar   +1 more source

An Improved SLIC Algorithm for Segmentation of Microscopic Cell Images

Biomedical Signal Processing and Control, 2022
Frank Jiang, Sai-Ho Ling
exaly  

KSLIC: K-mediods Clustering Based Simple Linear Iterative Clustering

Chinese Conference on Pattern Recognition and Computer Vision, 2019
Houwang Zhang, Yuan Zhu
semanticscholar   +1 more source

Semisupervised Classification Based on SLIC Segmentation for Hyperspectral Image

IEEE Geoscience and Remote Sensing Letters, 2020
Yuxiang Zhang, Yanni Dong, Ke Wu
exaly  

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