Advances in recent techniques for scientific data collection in the era of big data allow for the
systematic accumulation of large quantities of data at various data-capturing sites. Similarly …

Multi-view subspace clustering, which partitions multi-view data into their respective
underlying subspaces, has achieved the remarkable clustering performance by extracting …

Clustering is an unsupervised classical data processing technique, in which Fuzzy K-Means
is extensively researched in practical application owing to its efficiency. However, common …

Thermoplastic composites are regarded as a potential alternative to their thermoset
counterparts in aircraft industries owing to their cost-effective manufacturing process and …

The unsupervised nature of clustering has attracted significant interest. In particular,
researchers delve into exploring the superiority of fuzzy clustering in flexibly handling …

Multi-view data suffer from issues related to low quality and heterogeneity, which leads to
instability issues in existing learning models for clustering. To overcome the limitations of …

Recently, multi-view subspace clustering has attracted intensive attentions due to the
remarkable clustering performance by extracting abundant complementary information from …

Recently, multi-view high dimensional data obtained from diverse domains or various
feature extractors has drawn great attention due to its reflection of different properties or …

Computer vision and deep learning have made substantial progress in the areas of
agriculture and smart farming, particularly for enhancing crop production using image …

Considering that the improved possibilistic c-means (PCM) algorithms are sensitive to noise
while addressing the issue of consistency clustering in PCM, this paper proposes the …