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Due to the high dimensionality of hyperspectral data, dimension reduction is becoming an important problem in hyperspectral image classification. Band selection can retain the information which is capable of keeping the original meaning of the data, and thus has attracted more attention. This paper tackles the band selection problem from the perspective of multiple classifiers combination, which can...
The up-to-date researches focused on compressive sensing (CS) have indicated that a CS-based system could be very sensitive to signal noise which contaminates the input signal prior to measurement. In this paper, it is demonstrated that the SNR loss of the recovered signal can be estimated by the subsampling rate. The conditions based on which the proposed estimator is applied are theoretical analyzed...
An adaptive learning rate Backpropagation Neural Network (BPNN) is proposed to image segmentation of rice disease spots. Rice blast is a common disease of rice and is tested in this paper. Firstly, the combination of different color feature parameters is selected as the input of the BPNN. Secondly, a BPNN with 5 input, 10 hidden neurons and 1 output is constructed to rice blast spots segmentation...
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