Graph Based Multi-layer K-means++ (G-MLKM) for Sensory Pattern Analysis in Constrained Spaces

no code implementations • 21 Sep 2020 • Feng Tao, Rengan Suresh, Johnathan Votion, Yongcan Cao

Based on the dual graph and graph theory, we then generalize MLKM to G-MLKM by first understanding local data-target association and then extracting cross-local data-target association mathematically analyze the data association at intersections of that space.

Clustering

A Multi-Layer K-means Approach for Multi-Sensor Data Pattern Recognition in Multi-Target Localization

no code implementations • 30 May 2017 • Samuel Silva, Rengan Suresh, Feng Tao, Johnathan Votion, Yongcan Cao

Data-target association is an important step in multi-target localization for the intelligent operation of un- manned systems in numerous applications such as search and rescue, traffic management and surveillance.

Clustering Management

Multi-Sensor Data Pattern Recognition for Multi-Target Localization: A Machine Learning Approach

no code implementations • 28 Feb 2017 • Kasthurirengan Suresh, Samuel Silva, Johnathan Votion, Yongcan Cao

Data-target pairing is an important step towards multi-target localization for the intelligent operation of unmanned systems.

BIG-bench Machine Learning Clustering +1