Automated classification of single airborne particles from two-dimensional angle-resolved optical scattering (TAOS) patterns by non-linear filtering

Journal of Quantitative Spectroscopy and Radiative Transfer

Volumn 131, Issue , 2013, Pages 215-233

  Crosta, Giovanni Franco ^a   Pan, Yong Le ^b   Aptowicz, Kevin B ^c   Casati, Caterina ^a   Pinnick, Ronald G ^b   Chang, Richard K ^d   Videen, Gorden W ^b  

^a UNIVERSITY OF MILANO BICOCCA   (Italy)

^b U S ARMY RESEARCH LABORATORY   (United States)

^c WEST CHESTER UNIVERSITY   (United States)

^d Yale University   (United States)

Author keywords

Airborne particle; Angle resolved optical scattering; Bacillus subtilis; Feature extraction; Linear classifier; Machine learning; Outdoor sampling; Scattering pattern; Supervised training

Indexed keywords

AIRBORNE PARTICLE; ANGLE-RESOLVED OPTICAL SCATTERING; BACILLUS SUBTILIS; LINEAR CLASSIFIERS; SCATTERING PATTERN; SUPERVISED TRAININGS;

ALGORITHMS; ATMOSPHERIC AEROSOLS; EXPERIMENTS; FEATURE EXTRACTION; LEARNING SYSTEMS; MATHEMATICAL TRANSFORMATIONS; MULTIVARIANT ANALYSIS; REFRACTIVE INDEX; SCATTERING; TWO DIMENSIONAL;

LIGHT SCATTERING;

AEROSOL; ALGORITHM; FOURIER TRANSFORM; LIGHT SCATTERING; MULTIVARIATE ANALYSIS; PARTICLE SIZE;

BACILLUS SUBTILIS;

EID: 84886771766     PISSN: 00224073     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jqsrt.2013.06.009     Document Type: Article

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