"A privacy preservation framework for feedforward-designed convolutional ..."

De Li et al. (2022)

Details and statistics

DOI: 10.1016/J.NEUNET.2022.08.005

access: closed

type: Journal Article

metadata version: 2022-11-13

a service of  Schloss Dagstuhl - Leibniz Center for Informatics