FLIM-BoFP replaces per-block patch clustering in FLIM networks with a single input-level clustering step that creates a bag of feature points used to define filters across all encoder blocks, yielding faster training for parasite detection in optical microscopy.
IEEE Trans- actions on Image Processing30, 3804–3814 (2021)
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FLIM Networks with Bag of Feature Points
FLIM-BoFP replaces per-block patch clustering in FLIM networks with a single input-level clustering step that creates a bag of feature points used to define filters across all encoder blocks, yielding faster training for parasite detection in optical microscopy.