Quality detection method and system in fruit and vegetable drying process based on dynamic neural network
A dynamic neural network and drying process technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems such as low detection accuracy, and achieve the effect of improving prediction ability and detection accuracy.
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Embodiment 1
[0023] like figure 1 As shown in the figure, this embodiment provides a method for quality detection in the drying process of fruits and vegetables based on a dynamic neural network, including the following steps: Step S1: Collect and save the multi-spectral graphics of the fruit and vegetable slice sample set to be detected under multi-spectral and multiple frequency bands Step S2: preprocess the spectral graphics in the multispectral graphics set; Step S3: perform threshold segmentation on the processed image, and reconstruct the pixels of the region of interest after segmentation under each band in sequence as One-dimensional sequence; Step S4: perform zero-padded processing on the one-dimensional sequence under multiple bands of each sample in the sample set, and reconstruct the two-dimensional image, and increase the data dimension in the reconstructed two-dimensional image set by one dimension; Step S5: increase the The one-dimensional two-dimensional image set is sequen...
Embodiment 2
[0053] Based on the same inventive concept, this embodiment provides a dynamic neural network-based quality detection system for fruits and vegetables in the drying process. The principle of solving the problem is similar to the dynamic neural network-based quality detection method for fruits and vegetables in the drying process. No longer.
[0054] The present embodiment provides a quality detection system in the drying process of fruits and vegetables based on a dynamic neural network, including:
[0055] The acquisition module is used to collect and save the multi-spectral graphic set of the fruit and vegetable slice sample set to be detected under multi-spectral and multiple frequency bands;
[0056] a preprocessing module for preprocessing the spectral graphics in the multispectral graphics set;
[0057]The segmentation and reconstruction module is used to perform threshold segmentation on the processed image, and reconstruct the pixel points of the region of interest af...
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