Pham Huy Thong¹, Hoang Thi Canh^2,3,*, Nguyen Tuan Huy⁴, Nguyen Long Giang^1,*, Luong Thi Hong Lan⁴

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071776 - 12 January 2026

Abstract Satellite image segmentation plays a crucial role in remote sensing, supporting applications such as environmental monitoring, land use analysis, and disaster management. However, traditional segmentation methods often rely on large amounts of labeled data, which are costly and time-consuming to obtain, especially in large-scale or dynamic environments. To address this challenge, we propose the Semi-Supervised Multi-View Picture Fuzzy Clustering (SS-MPFC) algorithm, which improves segmentation accuracy and robustness, particularly in complex and uncertain remote sensing scenarios. SS-MPFC unifies three paradigms: semi-supervised learning, multi-view clustering, and picture fuzzy set theory. This integration allows the model to effectively… More >

Pham Huy Thong¹, Hoang Thi Canh^2,3,*, Luong Thi Hong Lan⁴, Nguyen Tuan Huy⁴, Nguyen Long Giang^1,*

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5461-5485, 2025, DOI:10.32604/cmc.2025.065127 - 19 May 2025

Abstract Multi-view clustering is a critical research area in computer science aimed at effectively extracting meaningful patterns from complex, high-dimensional data that single-view methods cannot capture. Traditional fuzzy clustering techniques, such as Fuzzy C-Means (FCM), face significant challenges in handling uncertainty and the dependencies between different views. To overcome these limitations, we introduce a new multi-view fuzzy clustering approach that integrates picture fuzzy sets with a dual-anchor graph method for multi-view data, aiming to enhance clustering accuracy and robustness, termed Multi-view Picture Fuzzy Clustering (MPFC). In particular, the picture fuzzy set theory extends the capability to… More >

Tran Manh Tuan^*, Tran Thi Ngan, Nguyen Tu Trung

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1241-1253, 2022, DOI:10.32604/csse.2022.024265 - 09 May 2022

Abstract In image processing, one of the most important steps is image segmentation. The objects in remote sensing images often have to be detected in order to perform next steps in image processing. Remote sensing images usually have large size and various spatial resolutions. Thus, detecting objects in remote sensing images is very complicated. In this paper, we develop a model to detect objects in remote sensing images based on the combination of picture fuzzy clustering and MapReduce method (denoted as MPFC). Firstly, picture fuzzy clustering is applied to segment the input images. Then, MapReduce is… More >