Automated Diatom Classification (Part B): A Deep Learning Approach-Reference-Cited by-同舟云学术

Automated Diatom Classification (Part B): A Deep Learning Approach

Published:2017-05-02 Issue:5 Volume:7 Page:460
ISSN:2076-3417
Container-title:Applied Sciences
language:en
Short-container-title:Applied Sciences

Author:

Pedraza Anibal,Bueno Gloria,Deniz Oscar,Cristóbal Gabriel,Blanco Saúl,Borrego-Ramos María

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Link

http://www.mdpi.com/2076-3417/7/5/460/pdf

Reference14 articles.

1. Directive 2000/60/EC. Establishing a Framework for Community Action in the Field of Water Policy,2000

2. Are biotic indices sensitive to river toxicants? A comparison of metrics based on diatoms and macro-invertebrates

3. The Diatoms: Applications for the Environmental and Earth Sciences;Smol,2010

4. Automated Diatom Classification (Part A): Handcrafted feature approaches;Bueno;Appl. Sci.,2017

5. Hierarchical classification of diatom images using ensembles of predictive clustering trees

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