Small sample underwater target identification method based on deep forest
A technology of underwater target and recognition method, which is applied in the direction of neural learning method, vibration measurement in fluid, measurement vibration, etc., can solve the problem of unsatisfactory target recognition in water, and achieve the effect of improving the recognition accuracy
Pending Publication Date: 2021-08-13
NORTHWESTERN POLYTECHNICAL UNIV
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Abstract
The invention provides a small sample underwater target identification method based on a deep forest. The method comprises the steps that the Mel-frequency cepstral coefficient MFCC features of an underwater target radiation noise signal is taken as the input data of a deep forest model; the deep forest model adopts a cascade structure of a forest to realize layer-by-layer processing of input data so as to perform characterization learning and perform prediction according to output of the last layer of the cascade forest, meanwhile, the number of layers of the cascade forest in the deep forest model is adaptively adjusted according to the data, the model complexity matches the data, and the method is suitable for small sample scenes. The method based on the deep forest provided by the invention can effectively improve the recognition accuracy of the underwater target under the small sample condition.
Application Domain
Vibration measurement in fluidNeural learning methods
Technology Topic
PhysicsAlgorithm +4
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