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NON-TRIVIAL FEATURE DERIVATION FOR INTENSIFYING FEATURE DETECTION USING LIDAR DATASETS THROUGH ALLOMETRIC AGGREGATION DATA ANALYSIS APPLYING DIFFUSED HIERARCHICAL CLUSTERING FOR DISCRIMINATING AGRICULTURAL LAND COVER IN PORTIONS OF NORTHERN MINDANAO,PHILIPPINES
Image classification OBIA LiDAR Allometric relations Non-trivial feature derivations Euclidean transformation
2016/12/1
Leaning on the derived results conducted by Central Mindanao University Phil-LiDAR 2.B.11 Image Processing Component, the paper attempts to provides the application of the Light Detection and Ranging ...
Cloud Model and Hierarchical Clustering based Spatial Data Mining Method and Application
Cloud Model Hierarchical Clustering Data Mining Weather Classification
2015/12/2
The paper proposed a method of weather classification based on cloud model and hierarchical clustering. Firstly, according to the weather sampling data from FY-2C images, cluster the brightness values...
Addendum to: An Approach to Hierarchical Clustering via Level Surfaces and Convexity
Hierarchical Clustering Level Sets Level Surfaces Radial Basis Function Convex Heat Gravity Light Cluster Validation Ridge Path Euclidean Distance Manhattan Distance Metric
2013/1/29
This article is an addendum to the 2001 paper [1] which investigated an approach to hierarchical clustering based on the level sets of a density function induced on data points in a d-dimensional feat...