Autoencoders, Kernels, and Multilayer Perceptrons for Electron Micrograph Restoration and Compression

• DOI: 10.48550/arxiv.1808.09916
• Publication Date: 2018-01-01
• Authors: Jeffrey M. Ede
• Keywords: Perceptron

We present 14 autoencoders, 15 kernels and multilayer perceptrons for electron micrograph restoration compression. These have been trained transmission microscopy (TEM), scanning (STEM) both (TEM+STEM). TEM autoencoders 1$\times$, 4$\times$, 16$\times$ 64$\times$ compression, STEM 4$\times$ compression TEM+STEM 2$\times$, 8$\times$, 16$\times$, 32$\times$ Kernels to approximate the denoising effect of autoencoders. input sizes 3, 5, 7, 11 fitted TEM, TEM+STEM. with 1 hidden layer 5 7 2 layers 7. 3 Our code, example usage pre-trained models are available at https://github.com/Jeffrey-Ede/Denoising-Kernels-MLPs-Autoencoders