Literature DB >> 22175934

Airborne particle classification with a combination of chemical composition and shape index utilizing an adaptive resonance artificial neural network.

Y Xie, P K Hopke, D Wienke.   

Abstract

Year:  1994        PMID： 22175934     DOI： 10.1021/es00060a024

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN： 0013-936X            Impact factor:   9.028


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  3 in total

1.  The effect of traction sanding on urban suspended particles in Finland.

Authors:  Kaarle Kupiainen; Heikki Tervahattu
Journal:  Environ Monit Assess       Date:  2004 Apr-May       Impact factor: 2.513

2.  Study of chemical composition and morphology of airborne particles in Chandigarh, India using EDXRF and SEM techniques.

Authors:  S G Sharma; M S N Srinivas
Journal:  Environ Monit Assess       Date:  2008-04-17       Impact factor: 3.307

3.  A transfer learning approach for improved classification of carbon nanomaterials from TEM images.

Authors:  Qixiang Luo; Elizabeth A Holm; Chen Wang
Journal:  Nanoscale Adv       Date:  2020-10-14
  3 in total

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