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Self-adaptive back propagation neural network (BPNN) models based on hierarchical clustering were developed to classify corn kernels. To generate the sample sets, randomly selected kernels were divided into seven classes using multiple clusters, including three classes of flat kernels, three classes of round kernels and abnormal class. Further, the stepwise discriminant analysis was conducted to select...
A novel morphological operator for scale space evaluation is introduced. The operator (X/sub B/)/sup B/ is less prone to object shrinkage and signal spreading than the Gaussian approach, and it treats similarly the intrusions and protrusions of the original image. Zero crossing migration with respect to this operation for various types of signal is derived. In order to track events efficiently from...
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