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Automatic identification of malaria and other red blood cell inclusions using convolutional neural networks
Angel Molina
, José Rodellar
, Laura Boldú
, Andrea Acevedo
, Santiago Alférez
, Anna Merino
urosario
Research output
:
Contribution to Journal
›
Research Article
›
peer-review
41
Scopus citations
Overview
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Keyphrases
Automatic Identification
100%
Cell Inclusions
100%
Convolutional Neural Network
100%
Deep Learning Model
20%
Digital Image
20%
Erythrocytes
40%
Infected Patients
20%
Machine Learning Techniques
20%
Malaria
100%
Malaria Parasite
40%
Malaria-infected Red Blood Cells
20%
Peripheral Blood Smear
20%
Red Blood Cells
100%
Serious Disease
20%
Transfer Learning
20%
Transformation Technique
20%
VGG16
20%
Watershed Transform
20%
Work Environment
20%
Immunology and Microbiology
Erythrocyte
66%
Hemocyte
100%
Plasmodium
66%
Transfer of Learning
33%
Biochemistry, Genetics and Molecular Biology
Hemocyte
100%
Plasmodium
66%
Transfer of Learning
33%