Robust active learning for the diagnosis of parasites

Pattern Recognition

Volumn 48, Issue 11, 2015, Pages 3572-3583

  Saito, Priscila T M ^a,b   Suzuki, Celso T N ^a,c   Gomes, Jancarlo F ^a   De Rezende, Pedro J ^a   Falcão, Alexandre X ^a  

^a UNIVERSITY OF CAMPINAS   (Brazil)

^b UNIVERSIDADE TECNOLÓGICA FEDERAL DO PARANÁ   (Brazil)

^c IMMUNOCAMP Research and Development of Technology   (Brazil)

Author keywords

Active learning; Automated diagnosis of intestinal parasites; Microscopy image analysis; Optimum path forest classifiers; Pattern recognition

Indexed keywords

ARTIFICIAL INTELLIGENCE; AUTOMATION; PATTERN RECOGNITION;

ACTIVE LEARNING; ACTIVE LEARNING METHODS; INTESTINAL PARASITES; LEARNING ITERATION; MICROSCOPY IMAGE ANALYSIS; OPTIMUM-PATH FORESTS; REALISTIC SCENARIO; STATE-OF-THE-ART APPROACH;

ITERATIVE METHODS;

EID: 84937812382     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2015.05.020     Document Type: Article

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