Multifrequency species classification of acoustic-trawl survey data using semi-supervised learning with class discovery.

Acoustic surveys often use multifrequency backscatter to estimate fish and plankton abundance. Direct samples are used to validate species classification of acoustic backscatter, but samples may be sparse or unavailable. A generalized Gaussian mixture model was developed to classify multifrequency acoustic backscatter when not all species classes are known. The classification, based on semi-supervised learning with class discovery, was applied to data collected in the eastern Bering Sea during summers 2004, 2007, and 2008. Walleye pollock, euphausiids, and two other major classes occurring in the upper water column were identified.

[1]  John K. Horne,et al.  Acoustic approaches to remote species identification: a review , 2000 .

[2]  Sebastian Thrun,et al.  Text Classification from Labeled and Unlabeled Documents using EM , 2000, Machine Learning.

[3]  M. Trevorrow,et al.  Comparison of multifrequency acoustic and in situ measurements of zooplankton abundances in Knight Inlet, British Columbia. , 2005, The Journal of the Acoustical Society of America.

[4]  Alex De Robertis,et al.  Development and application of an empirical multifrequency method for backscatter classification , 2010 .

[5]  C I H Anderson,et al.  Classifying multi-frequency fisheries acoustic data using a robust probabilistic classification technique. , 2007, The Journal of the Acoustical Society of America.

[6]  Gérard Govaert,et al.  Assessing a Mixture Model for Clustering with the Integrated Completed Likelihood , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  David J. Miller,et al.  A Mixture Model and EM-Based Algorithm for Class Discovery, Robust Classification, and Outlier Rejection in Mixed Labeled/Unlabeled Data Sets , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Geoffrey J. McLachlan,et al.  Discriminant Analysis and Statistical Pattern Recognition: McLachlan/Discriminant Analysis & Pattern Recog , 2005 .

[9]  Geir Odd Johansen,et al.  Acoustic species identification of schooling fish , 2009 .

[10]  Paul G. Fernandes,et al.  Classification trees for species identification of fish-school echotraces , 2009 .

[11]  Alex De Robertis,et al.  A post-processing technique to estimate the signal-to-noise ratio and remove echosounder background noise , 2007 .