The proposed All-MLP decoder consists of four main steps. First, multi-level features Fi from the MiT encoder go through an MLP layer to unify the channel dimension. Then, in a second step, features are up-sampled to 1/4th and concatenated together. Third, a MLP layer is adopted to fuse the concatenated features F. Finally, another MLP layer takes the fused feature to predict the segmentation mask M with a H 4 × W 4 × Ncls resolution, where Ncls is the number of categories. This lets us formulate the decoder as: Fˆ i = Linear(Ci , C)(Fi), ∀i Fˆ i = Upsample( W 4 × W 4 )(Fˆ i), ∀i F = Linear(4C, C)(Concat(Fˆ i)), ∀i M = Linear(C, Ncls)(F), (4) where M refers to the predicted mask, and Linear(Cin, Cout)(·) refers to a linear layer with Cin and Cout as input and output vector dimensions respectively.翻译

时间: 2023-06-19 07:09:19 浏览: 162
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An efficient multi-standard QC-LDPC decoder based on the row-layered decoding algorithm

提出的All-MLP解码器包括四个主要步骤。首先，来自MiT编码器的多级特征Fi通过MLP层进行处理，以统一通道维度。然后，在第二步中，特征被上采样到1/4并连接在一起。第三步采用MLP层来融合连接的特征F。最后，另一个MLP层将融合的特征传递给预测分割掩码M，其分辨率为H 4×W 4×Ncls，其中Ncls是类别数。这使我们可以将解码器公式化为：Fˆ i = Linear(Ci , C)(Fi)，∀i Fˆ i = Upsample( W 4×W 4 )(Fˆ i)，∀i F = Linear(4C, C)(Concat(Fˆ i))，∀i M = Linear(C, Ncls)(F)，(4) 这里M是预测的掩码，Linear(Cin，Cout)(·)是具有Cin和Cout作为输入和输出向量维度的线性层。
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