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A Hyperheuristic Approach for Unsupervised Land-Cover Classification
(Ieee-inst Electrical Electronics Engineers Inc, 2016-06-01)
Unsupervised land-use/cover classification is of great interest, since it becomes even more difficult to obtain high-quality labeled data. Still considered one of the most used clustering techniques, the well-known k-means ...
Infected Fruit Part Detection using K-Means Clustering Segmentation Technique
Nowadays, overseas commerce has increased drastically in many countries. Plenty fruits are imported from the other nations such as oranges, apples etc. Manual identification of defected fruit is very time consuming. This ...
Push Recovery for Humanoid Robot in Dynamic Environment and Classifying the Data Using K-Mean
Push recovery is prime ability that is essential to
be incorporated in the process of developing a robust humanoid
robot to support bipedalism. In real environment it is very
essential for humanoid robot to maintain ...
Building detection from lidar data using entropy and the k-means concept
(2019-06-04)
Information obtained from LiDAR data processing is considered in a variety of applications, among them urban planning. In this context, buildings play a substantial role, since a high percentage of the urban landscape is ...
Novas estratégias para conserto de soluções degeneradas no algoritmo k-means
(BrasilUFRNPROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA ELÉTRICA E DE COMPUTAÇÃO, 2016-10-05)
QK-Means: A Clustering Technique Based on Community Detection and K-Means for Deployment of Cluster Head Nodes
(Ieee, 2012-01-01)
Wireless Sensor Networks (WSN) are a special kind of ad-hoc networks that is usually deployed in a monitoring field in order to detect some physical phenomenon. Due to the low dependability of individual nodes, small radio ...