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Adaptive enhanced interval type-2 possibilistic fuzzy local information clustering with dual-distance for land cover classification
C Wu, X Guo - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Land cover classification of remote sensing image is faced with uncertainties such as
“significant difference in category density”,“the same object with different spectra”, and …
“significant difference in category density”,“the same object with different spectra”, and …
Deep multi-look sequence processing for synthetic aperture sonar image segmentation
Deep learning has enabled significant improvements in semantic image segmentation,
especially in underwater imaging domains such as side scan sonar (SSS). In this work, we …
especially in underwater imaging domains such as side scan sonar (SSS). In this work, we …
Total Bregman divergence-driven possibilistic fuzzy clustering with kernel metric and local information for grayscale image segmentation
C Wu, X Zhang - Pattern Recognition, 2022 - Elsevier
Kernel possibilistic fuzzy C-means with local information (KWPFLICM) has important
research significance of image segmentation, but it is very sensitive to high noise or outliers …
research significance of image segmentation, but it is very sensitive to high noise or outliers …
A novel kernelized total Bregman divergence-driven possibilistic fuzzy clustering with multiple information constraints for image segmentation
C Wu, X Zhang - IEEE Transactions on Fuzzy Systems, 2021 - ieeexplore.ieee.org
Aiming at the problem that existing robust fuzzy clustering algorithms are still sensitive to
high noise, a total Bregman divergence-driven possibilistic fuzzy clustering with multiple …
high noise, a total Bregman divergence-driven possibilistic fuzzy clustering with multiple …
Interval Type-2 enhanced possibilistic fuzzy C-means noisy image segmentation algorithm amalgamating weighted local information
C Huang, H Lei, Y Chen, J Cai, X Qin, J Peng… - … Applications of Artificial …, 2024 - Elsevier
The fuzzy clustering algorithms based on interval type-2 are effective methods for data
clustering and image segmentation with some potential advantages in dealing with higher …
clustering and image segmentation with some potential advantages in dealing with higher …
Histogram Layers for Neural Engineered Features
J Peeples, SA Kharsa, L Saleh, A Zare - ar**
Y Arhant, OL Tellez, X Neyt… - IEEE Journal of Selected …, 2024 - ieeexplore.ieee.org
Seabed characterization consists in the study of the physical and biological properties of the
of ocean floors. Sonar is commonly employed to capture the acoustic backscatter reflected …
of ocean floors. Sonar is commonly employed to capture the acoustic backscatter reflected …
[Retracted] Application of a Fuzzy Information Analysis and Evaluation Method in the Development of Regional Rural e‐Commerce
L Wang - Advances in Multimedia, 2022 - Wiley Online Library
As a new form of e‐commerce, digital industry will become a tool to enhance regional
competitiveness and win the allocation of resources, and its advanced degree is the …
competitiveness and win the allocation of resources, and its advanced degree is the …
Comparison of possibilistic fuzzy local information c-means and possibilistic k-nearest neighbors for synthetic aperture sonar image segmentation
Synthetic aperture sonar (SAS) imagery can generate high resolution images of the seafloor.
Thus, segmentation algorithms can be used to partition the images into different seafloor …
Thus, segmentation algorithms can be used to partition the images into different seafloor …
Investigation of Time-Frequency Feature Combinations with Histogram Layer Time Delay Neural Networks
While deep learning has reduced the prevalence of manual feature extraction,
transformation of data via feature engineering remains essential for improving model …
transformation of data via feature engineering remains essential for improving model …