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An Attention‐Assisted Machine Learning System for Deep Microorganism Image Classification

open access: yesAdvanced Intelligent Systems, EarlyView.
An attention‐assisted DenseNet201 framework was developed for the classification of eight microorganism classes from microscopic images. The proposed model improved classification performance and achieved an accuracy of 87.38%. Advances in microbiology and environmental health fundamentally depend on precise and timely microorganism identification ...
Yujie Li   +6 more
wiley   +1 more source

Multiscale-Aware Graph Embedding Approach Uncovers LC-61, a Potent Anti-<i>Leishmania infantum</i> Compound. [PDF]

open access: yesJ Chem Inf Model
Costa VAF   +12 more
europepmc   +1 more source

Intelligent identification of medical and veterinary intracellular protozoa by using self-supervised learning. [PDF]

open access: yesParasit Vectors
Kittichai V   +5 more
europepmc   +1 more source

Cell-MICS: Detecting Immune Cells With Label-Free Two-Photon Autofluorescence and Deep Learning. [PDF]

open access: yesJ Biophotonics
Kreiss L   +9 more
europepmc   +1 more source

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