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. 2021 Jan 20;21(3):686. doi: 10.3390/s21030686

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© 2021 by the authors.

Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

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The framework of the PFAN for image classification we propose. Once {C₁, C₂, C₃, C₄} has been obtained, we further generate the hidden layer H_f, and then D₁, D₂... progressively. “” denotes down-sampling implemented by 2 × 2 MaxPooling and “” denotes an element-wise sum. In the dashed rectangle, the horizontal arrow represents the bottleneck or the basic block operation, and the diagonally downward arrow indicates down-sampling implemented by 2 × 2 MaxPooling. Arrows outside the rectangle only represent the data flow direction.

Inline graphic — The framework of the PFAN for image classification we propose. Once {C₁, C₂, C₃, C₄} has been obtained, we further generate the hidden layer H_f, and then D₁, D₂... progressively. “” denotes down-sampling implemented by 2 × 2 MaxPooling and “” denotes an element-wise sum. In the dashed rectangle, the horizontal arrow represents the bottleneck or the basic block operation, and the diagonally downward arrow indicates down-sampling implemented by 2 × 2 MaxPooling. Arrows outside the rectangle only represent the data flow direction.