if you use fuzzy-c-means package in your paper, please cite it in your publication. @software{dias2019fuzzy, author = {Madson Luiz Dantas Dias}, title = {fuzzy-c ...

Abstract: This article introduces the Bayesian probabilistic fuzzy neural network (BPFNN), a unified architecture designed to overcome the challenges of conventional ...

Multimodal remote sensing data, such as hyperspectral and LiDAR imagery, provide complementary information for land cover analysis. However, effectively clustering these heterogeneous yet spatially ...

Clustering is a core pillar of machine learning. To understand how systems can group similar information without being told what to look for, you must start with the basics of Clustering Algorithms.

Image segmentation is a fundamental process in digital image analysis, with applications in object recognition, medical imaging, and computer vision. Traditional segmentation techniques often struggle ...

My journey with R and Python started off quite challenging, but thanks to LLM tools (ChatGPT, Gemini, etc.), programming has become much more accessible. More importantly, I’ve been seeing firsthand ...

Not uncommonly, the emergence of the quantum phenomenon accompanies dominant states that are not spatially homogeneous 1. This situation is generally originated from the cooperative interplay among ...

Fiber clustering methods are typically used in brain research to study the organization of white matter bundles from large diffusion MRI tractography datasets. These methods enable exploratory bundle ...

The present work aims to explore the performance of fuzzy system-based medical image processing for predicting the brain disease. The imaging mechanism of NMR (Nuclear Magnetic Resonance) and the ...

In conversation, prosody complements words, forming a structured communication system distinct from, yet connected to, text. By analyzing large datasets of spontaneous conversations and clustering ...