Prof. Dr. Alexander S. Ecker

Name Card

Main Affiliation
 
Staff Status
unigoe
 

1-9 of 9
 
The bibliographical data in your publication list are complete
You can correct existing data in the blue highlighted fields.To do this, please click on the coloured field. It is not possible to delete data here.
Fields that are not marked in colour (e. g. the authors) can be edited using the input form. To do so, click on the in front of the respective publication.
The bibliographic data in your publication list may be incomplete. You can
  • add any missing data in the fields marked in red or
  • correct existing data in the blue highlighted fields.
To do this, please click on the coloured field. It is not possible to delete data here.
Fields that are not marked in colour (e. g. the authors) can be edited using the input form. To do so, click on the in front of the respective publication.
Check/Uncheck all
  • 2017 | Conference Paper
    ​ ​Mixed latent variable model of attention in V1​
    Vinogradov, O. & Ecker, A. S. ​ (2017)
    pp. 242​-243. , Göttingen.
    ​Details 
  • 2017 | Preprint
    ​ ​Synthesising Dynamic Textures using Convolutional Neural Networks​
    Funke, C. M.; Gatys, L. A.; Ecker, A. S.  & Bethge, M.​ (2017)
    ​Details  arXiv 
  • 2017 | Preprint
    ​ ​Neural system identification for large populations separating "what" and "where"​
    Klindt, D. A.; Ecker, A. S. ; Euler, T.& Bethge, M.​ (2017)
    ​Details  arXiv 
  • 2017 | Conference Paper
    ​ ​Controlling Perceptual Factors in Neural Style Transfer​
    Gatys, L. A.; Ecker, A. S. ; Bethge, M.; Hertzmann, A. & Shechtman, E.​ (2017)
    ​2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) pp. 3730​-3738. ​2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)​, Honolulu, HI, USA. DOI: https://doi.org/10.1109/CVPR.2017.397 
    ​Details  DOI 
  • 2017 | Preprint
    ​ ​A parametric texture model based on deep convolutional features closely matches texture appearance for humans​
    Wallis, T. S. A.; Funke, C. M.; Ecker, A. S. ; Gatys, L. A.; Wichmann, F. A.& Bethge, M.​ (2017). DOI: https://doi.org/10.1101/165761 
    ​Details  DOI 
  • 2017 | Journal Article
    ​ ​Towards matching peripheral appearance for arbitrary natural images using deep features​
    Wallis, T.; Funke, C.; Ecker, A. ; Gatys, L.; Wichmann, F. & Bethge, M.​ (2017) 
    Journal of Vision, 17(10) art. 786​.​ DOI: https://doi.org/10.1167/17.10.786 
    ​Details  DOI 
  • 2017 | Journal Article
    ​ ​A parametric texture model based on deep convolutional features closely matches texture appearance for humans​
    Funke, C.; Wallis, T.; Ecker, A. S. ; Gatys, L.; Wichmann, F. & Bethge, M.​ (2017) 
    Journal of Vision, 17(10) art. 1081​.​ DOI: https://doi.org/10.1167/17.10.1081 
    ​Details  DOI 
  • 2017 | Journal Article
    ​ ​A parametric texture model based on deep convolutional features closely matches texture appearance for humans​
    Wallis, T. S. A.; Funke, C. M.; Ecker, A. S. ; Gatys, L. A.; Wichmann, F. A. & Bethge, M.​ (2017) 
    Journal of Vision, 17(12) art. 5​.​ DOI: https://doi.org/10.1167/17.12.5 
    ​Details  DOI  PMID  PMC 
  • 2017 | Journal Article
    ​ ​Texture and art with deep neural networks​
    Gatys, L. A.; Ecker, A. S.   & Bethge, M.​ (2017) 
    Current Opinion in Neurobiology, 46 pp. 178​-186​.​ DOI: https://doi.org/10.1016/j.conb.2017.08.019 
    ​Details  DOI  PMID  PMC 

Publication List

All Articles (Book & Journal) Conference objects Books & Book chapters Book chapters & Review Lectures & Poster Articles & Preprints Papers (Journal & Conference)

Filter

Active filter:
Date Issued:  [2010 TO 2019]
Date Issued:  2017

Type

Author

Language

Fulltext

Options

Citation Style

GRO View APA Chicago MLA Vancouver
https://publications.goettingen-research-online.de URI: /cris/rp/rp114418
ID: 0000000
PREF: default TOKEN:

0

Sort

Issue Date
ASC DESC
Title
ASC DESC

Embed

JavaScript
Link

Export

Activate Export Mode
Deactivate Export Mode

Select some or all items (max. 800 for CSV/Excel) from the publications list, then choose an export format below.