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Abstract
Abstract A new super-resolution (SR) technique by CNNs is introduced: Lightweight Duplication Super Resolution Network (LDPSR). This network achieves performance similar to mainstream non-lightweight network networks while maintaining a lower calculation cost and number of parameters, and has specially designed a Lightweight Duplication Plugin (LDP), which only generates addition operations without increasing the burden of multiplication operations, effectively improving the computational performance of the network. This plugin greatly reduces the network size by segmenting input images and expanding them separately to avoid increasing the parameter count. The network architecture includes a shallow part, a deep part, and an up-sampling part. By combining special convolution modules and lightweight plugins, the diversity of features is enhanced while controlling the parameters and costs of computational. This study provides a new network architecture and computing method that can achieve efficient SR on lightweight devices with lower computational costs and parameter requirements, to achieve the practical application value of SR technology.
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