Combining max-pooling and wavelet pooling strategies for semantic image segmentation
作者：
Highlights：
• A new multi-pooling strategy combining wavelet and traditional pooling.
• A new version of Segnet, named MPSegnet, using the new multi-pooling strategy.
• A two-stream architecture that combines the Segnet network with MPSegnet.
• The multi-pooling scheme efficiency was verified using complexity and visual analysis.
• Experiments showing that our methods are comparable to the state-of-the-art.
摘要
•A new multi-pooling strategy combining wavelet and traditional pooling.•A new version of Segnet, named MPSegnet, using the new multi-pooling strategy.•A two-stream architecture that combines the Segnet network with MPSegnet.•The multi-pooling scheme efficiency was verified using complexity and visual analysis.•Experiments showing that our methods are comparable to the state-of-the-art.
论文关键词：Convolutional neural networks,Semantic segmentation,Max pooling,Wavelet pooling,IRRG images
论文评审过程：Received 7 December 2020, Revised 10 May 2021, Accepted 9 June 2021, Available online 12 June 2021, Version of Record 17 June 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.115403
