An online clustering framework with dynamic cluster splitting/merging and fixed-size representative sampling achieves about 0.68 average F1 on three seafloor image datasets with bounded runtime.
Autonomous data stream clustering implementing split-and-merge concepts–towards a plug-and- play approach,
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Online Clustering of Seafloor Imagery for Interpretation during Long-Term AUV Operations
An online clustering framework with dynamic cluster splitting/merging and fixed-size representative sampling achieves about 0.68 average F1 on three seafloor image datasets with bounded runtime.