"PIP-Net: Patch-Based Intuitive Prototypes for Interpretable Image ..."

Meike Nauta et al. (2023)

> Home

Details and statistics

DOI: 10.1109/CVPR52729.2023.00269

access: closed

type: Conference or Workshop Paper

metadata version: 2023-08-28

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/cvpr/NautaSKS23
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/cvpr/NautaSKS23
Meike Nauta, Jörg Schlötterer, Maurice van Keulen, Christin Seifert:
PIP-Net: Patch-Based Intuitive Prototypes for Interpretable Image Classification. CVPR 2023: 2744-2753

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.