Cluster analysis is a crucial technique in unsupervised machine learning, pattern recognition, and data analysis. However, current clustering algorithms suffer from the need for manual determination of parameter values, low accuracy, inconsistent performance concerning size structure. To address these challenges, novel algorithm called fully automated density-based method (FADBC) proposed. The ...

Clustering combination uses more than one clustering method with identical pattern features to improve the clustering performance. In general clustering is an optimization procedure based on a specific clustering criterion, so clustering combination can be regarded as a technique that constructs and processes multiple clustering criteria rather than a single criterion. We propose two methods of...

Objective: In view of contemporary panoramic camera-laser scanner system, the accuracy of traditional calibration method based on the target feature is not stable and multiple calibrations are needed. The method based on statistical optimization has the disadvantage that the requirement of the number of laser scanner’s channels is relatively high. Calibration equipments with extreme accuracy fo...

Introduction Patient-specific models of maxillofacial musculature would be of great use in evaluation of prospective surgical treatment options. Due to complex fibre interactions and low image SNR within this region, both diffusion tensor MRI (DT-MRI [1]) and diffusion spectrum imaging [2] have been precluded from use despite previous application to large muscles (due to inability to resolve cr...

This paper introduces a novel method for ultrasound calibration for both spatial and temporal parameters. The main advantage of this method is that it does not require a phantom, which is usually expensive to fabricate. Furthermore, the method does not require extensive image processing. For spatial calibration, we solve an optimization problem established by a set of equations that relate the ...

Given quantization and clustering classification of the deviations between TM and ETM+ multibandwidth images based on approved thresholds, a calibration algorithm for the correlation coefficient in multi-bandwidth images is suggested in this paper. This experiment detected strong and proportional correlation relationship between the highest area of land surface temperature and the lowest area o...

This paper presents a new hybrid fuzzy clustering method. In the proposed method, cluster prototypes are values that minimize the introduced generalized cost function. The proposed method can be considered as a generalization of fuzzy c-means (FCM) method as well as the fuzzy c-median (FCMed) clustering method. The generalization of the cluster cost function is made by applying the Lp norm. The...

One of the main techniques used in data mining is data clustering, which has many applications in computer science, biology, and social sciences. Constrained clustering is a type of clustering in which side information provided by the user is incorporated into current clustering algorithms. One of the well researched constrained clustering algorithms is called microaggregation. In a microaggreg...