Transposed convolution layer. Jul 23, 2025 · A transposed convolutional layer is an upsampling layer that generates the output feature map greater than the input feature map. Sep 29, 2022 · This blog is about what are Upsampling and Transposed Convolutions layers and how they works. Image by author. It is similar to a deconvolutional layer. For example, when specifying the padding number on either side of the height and width as 1, the first and last rows and columns will be removed from the transposed convolution output. This layer performs the transpose of convolution and does not perform deconvolution. 2. This layer is sometimes incorrectly known as a "deconvolution" or "deconv" layer. The need for transposed convolutions generally arise from the desire to use a transformation going in the opposite direction of a normal convolution, i. 10. ve q5zx s0agz6 yuonxh 2mkv w5 saq pp aw 5jgq