Detection of new construction land change based on attention intensive connection pyramid network

doi:10.13474/j.cnki.11-2246.2022.0075

Abstract

Abstract: To settle the problems of frequent and rapid changes of new urban construction sites and complex scenarios which lead to under-segmentation or over-segmentation of change detection results,this paper proposes a densely connected pyramid network with a fused attention mechanism for urban new construction site change detection.In the coding stage,a convolutional attention model is applied to enhance the attention to change information and highlight important features;then a densely connected null convolutional spatial pyramid pooling module is used to realize the extraction and fusion of multi-scale features and improves the feature utilization and propagation efficiency;in the decoding stage,the spatial scale features of the image are restored by upsampling the extracted feature maps.The experimental results show that the method in this paper effectively improves the under-segmentation and oversegmentation problems,and the change detection effect is better.

Key words: attention mechanism;dense connection pyramid;encoding and decoding;new construction land;change detection

CLC Number:

P237

PAN Jianping, LI Xin, SUN Bowen, HU Yong, LI Mingming. Detection of new construction land change based on attention intensive connection pyramid network[J]. Bulletin of Surveying and Mapping, 2022, 0(3): 41-46,59.

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