Quantifying California current plankton samples with efficient machine learning techniques

OCEANS 2015 - MTS/IEEE Washington

Volumn , Issue , 2016, Pages

  Ellen, Jeffrey ^a   Li, Hongyu ^a   Ohman, Mark D ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

image analysis; machine learning; zooplankton; Zooscan

Indexed keywords

IMAGE ANALYSIS; LEARNING SYSTEMS; PLANKTON;

CALIFORNIA CURRENT; ENSEMBLE OF MODELS; GEOMETRIC FEATURE; LABELED IMAGES; MACHINE LEARNING TECHNIQUES; SIZE FRACTIONATION; ZOOPLANKTON; ZOOSCAN;

MACHINE LEARNING;

EID: 84963976278     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.23919/oceans.2015.7404607     Document Type: Conference Paper

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