Evaluating the Faithfulness of Saliency Maps in Explaining Deep Learning Models Using Realistic Perturbations

AuthID
 P-00X-N35
5
Author(s)
Amorim, JP
·
Cortes, M
·
Vila, V
Tipo de Documento
Article
Year published
2023
Publicado
in INFORMATION PROCESSING & MANAGEMENT, ISSN: 0306-4573
Volume: 60, Número: 2, Páginas: 103225 (14)
Indexing
Wos®
Scopus®
Dblp®/pt/publications/view/971877
Crossref®11
Google Scholar®
Publication Identifiers
DBLP: journals/ipm/AmorimASCV23
SCOPUS: 2-s2.0-85144325667
Wos: WOS:000911042300001
Source Identifiers
ISSN: 0306-4573
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