Unsupervised clustering of high spatial resolution remote-sensing images plays a significant
role in detailed land-cover identification, especially for agricultural and environmental …

Spectral clustering is able to extract clusters with various characteristics without a parametric
model, however it is infeasible for large datasets due to its high computational cost and …

Spectral clustering (SC) has been commonly used in recent years, thanks to its
nonparametric model, its ability to extract clusters of different manifolds and its easy …

The neural gas has been successfully used for prototype based clustering approaches. Its
topology based quantization effectively aids in approximate spectral clustering (ASC) to …

Two commonly used neural networks for vector quantization based analysis of high-
dimensional large datasets are the self-organizing map (SOM) and neural gas (NG). Owing …

Considering the economic and environmental aspects, hazelnut orchards are of great
importance in Turkey. It is crucial to develop methods for detecting, monitoring, protecting …

The involvement of human interactions with business processes through Enterprise Social
Networks improves organizations performance. However, Enterprise Social Networks …

The upswing of big data and cloud storage services brings along a myriad of possibilities to
compare data points on a large scale. However, privacy concerns may limit the applications …

Fast and accurate analysis of medical data is of great importance for diagnosis and
treatment. In line with the technological developments, the size and diversity of these data …

Özet Öbekleme, eğitmensiz bir yöntem olarak, herhangi veri sınıflandırmasında veya verinin
gerçek öbeklerinin bulunmasında kullanılmaktadır. Örneğin, gözlem, veri, özellik vektörü gibi …