Division and identification method and device based on dense network image

The invention provides a division and identification method and device based on a dense network image and relates to the technical field of neural networks. The division and identification method based on the dense network image comprises the following steps: firstly, capturing layering features of the dense network image by taking a convolutional layer as a feature extracting device; inputting obtained multi-scale feature patterns into an encoding module; meanwhile, connecting feature patterns with different scales with the feature patterns with the corresponding scales in the encoding moduleby utilizing jumping connection; carrying out down-sampling and semantic feature extraction on the feature patterns by applying the encoding module; carrying out up-sampling on the feature patterns by applying a decoding module and recovering detailed information to obtain the multi-scale feature patterns; then carrying out chain type residual error pooling operation on an output feature patternobtained by dense deconvol