Learning competitive channel-wise attention in residual network with masked regularization and signal boosting

作者:

Highlights:

• Some strategies are proposed to jointly model the relationship of residual and identity channels.

• A masked regularization and a signal boosting method are proposed to improve diversity of features.

• These methods can be cheaply applied to residual networks.

摘要

•Some strategies are proposed to jointly model the relationship of residual and identity channels.•A masked regularization and a signal boosting method are proposed to improve diversity of features.•These methods can be cheaply applied to residual networks.

论文关键词:Residual networks,Competitive channel-wise attention,Masked regularization,Signal boosting

论文评审过程:Received 10 May 2019, Revised 8 February 2020, Accepted 21 May 2020, Available online 30 May 2020, Version of Record 29 June 2020.

论文官网地址:https://doi.org/10.1016/j.eswa.2020.113591

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