Twin network change detection model based on deep learning
A twin network and change detection technology, applied in the field of change detection, can solve the problems of small amount of data, time-consuming, expensive, etc., and achieve the effect of improving model accuracy and improving the ability to extract differential features
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[0032] The present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments.
[0033] like figure 1 As shown, this embodiment discloses a deep learning-based Siamese network change detection model, which includes two modules: a generator and a discriminator, and the generator is a dual-branch computing model for acquiring difference images. We know that the generator includes two parts: the encoder and the decoder. In this scheme, ResNet18 is used as the model encoder to extract image feature information, and the encoder is transformed with a twin network. The parameters of the two ResNet18 networks are shared for extraction A phase characteristic map of a phase. by the second branch convolutional network ( figure 1 middle ) and an upsampling convolutional network to form a decoder, the second branch convolutional network is used to calculate the difference feature map according to the two phase feature maps...
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