Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

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

Tools
- Tools
+ Tools

Ede, Jeffrey M. (2018) Autoencoders, Kernels, and Multilayer Perceptrons for Electron Micrograph Restoration and Compression. Working Paper. Department of Physics ; University of Warwick. (Unpublished)

Research output not available from this repository, contact author.
Official URL: https://arxiv.org/abs/1808.09916

Request Changes to record.

Abstract

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

Item Type: Working or Discussion Paper (Working Paper)
Divisions: Faculty of Science > Physics
Journal or Publication Title: arXiv preprint arXiv:1808.09916
Publisher: Department of Physics ; University of Warwick
Official Date: 2018
Dates:
DateEvent
2018Updated
Number: 1808.09916
Institution: University of Warwick
Status: Not Peer Reviewed
Publication Status: Unpublished
Access rights to Published version: Open Access
Description:

Sets of autoencoders, convolution kernels, and multilayer perceptrons. They can be used for denoising or data compression.

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item
twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us