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Jan 2, 2020 · In this paper, the lightweight residual densely connected blocks are proposed to guaranty the deep supervision, efficient gradient flow, and feature reuse ...
Jul 4, 2020 · In this paper, the lightweight residual densely connected blocks are proposed to guaranty the deep supervision, efficient gradient flow, and feature reuse ...
The lightweight residual densely connected blocks are proposed to guaranty the deep supervision, efficient gradient flow, and feature reuse abilities of ...
The proposed method decreases the cost of training and inference processes without using any special hardware-software equipment by just reducing the number of ...
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Lightweight residual densely connected convolutional neural network. https://doi.org/10.1007/s11042-020-09223-8 ·. Journal: Multimedia Tools and Applications ...
In this paper, the residual densely connected blocks are proposed to guaranty the deep supervision, efficient gradient flow, and feature reuse abilities of ...
In this paper, the lightweight residual densely connected blocks are proposed to guaranty the deep supervision, efficient gradient flow, and feature reuse ...
In this paper, a new module named Densely Connected Residual Module is presented to effectively decrease the number of parameters in our network. We introduce ...
Jul 1, 2023 · A novel single-branch, single-scale lightweight convolutional neural network, named SDRCNN, is developed in this study. By using a novel dense ...
This paper proposes a lightweight Densely Connected and Inter-Sparse Convolutional Networks with aggregated Squeeze-and-Excitation transformations (DenisNet-SE)