Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/40333| Title: | Evaluating Feature Attribution Methods in the Image Domain: High-Dimensional Datasets | Data Creator - person: | Gevaert, Arne ROUSSEAU, Axel-Jan BECKER, Thijs VALKENBORG, Dirk De Bie, Tijl Saeys, Yvan |
Data Creator - organization: | Ghent University Hasselt University |
Data Curator - person: | Gevaert, Arne | Data Curator - organization: | Ghent University | Rights Holder - person: | Gevaert, Arne | Rights Holder - organization: | Ghent University | Publisher: | Zenodo | Issue Date: | 2022 | Abstract: | Here you can find the versions of the Places-365 and Caltech-256 datasets used in the paper Evaluating Feature Attribution Methods in the Image Domain. | Research Discipline: | Natural sciences > Information and computing sciences > Visual computing > Computer vision (01020902) | Keywords: | Computer Vision;Pattern Recognition;Machine learning | DOI: | 10.5281/zenodo.6221586 | Link to publication/dataset: | https://zenodo.org/record/6221586 | Source: | Zenodo. 10.5281/zenodo.6221586 https://zenodo.org/record/6221586 | Publications related to the dataset: | 10.48550/arXiv.2202.12270 | License: | Creative Commons Attribution 4.0 International (CC-BY-4.0) | Access Rights: | Open Access | Version: | 1.0 | Category: | DS | Type: | Dataset |
| Appears in Collections: | Datasets |
Show full item record
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.