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Browsing by Subject "DBSCAN"

Browsing by Subject "DBSCAN"

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  • Nanda S.J.; Panda G. (2015)
    The basic DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm uses minimum number of input parameters, very effective to cluster large spatial databases but involves more computational complexity. ...
  • Sharma T.; Rajurkar S.D.; Molangur N.; Verma N.K.; Salour A. (2019)
    Herein, an approach is presented to count objects in an image with different viewpoints. The multiple views of prototype have been used to get the viewpoint invariance in Speeded Up Robust Feature. For each view, presence ...