date: 2023-09-21T13:30:55Z pdf:PDFVersion: 1.7 pdf:docinfo:title: A novel feature-scrambling approach reveals the capacity of convolutional neural networks to learn spatial relations xmp:CreatorTool: Elsevier access_permission:can_print_degraded: true subject: Neural Networks, 167 (2023) 400-414. doi:10.1016/j.neunet.2023.08.021 language: en-US dc:format: application/pdf; version=1.7 pdf:docinfo:custom:robots: noindex pdf:docinfo:creator_tool: Elsevier access_permission:fill_in_form: true pdf:encrypted: false dc:title: A novel feature-scrambling approach reveals the capacity of convolutional neural networks to learn spatial relations modified: 2023-09-21T13:30:55Z cp:subject: Neural Networks, 167 (2023) 400-414. doi:10.1016/j.neunet.2023.08.021 pdf:docinfo:custom:CrossMarkDomains[1]: sciencedirect.com robots: noindex pdf:docinfo:subject: Neural Networks, 167 (2023) 400-414. doi:10.1016/j.neunet.2023.08.021 pdf:docinfo:creator: Amr Farahat PTEX.Fullbanner: This is pdfTeX, Version 3.14159265-2.6-1.40.21 (TeX Live 2020) kpathsea version 6.3.2 meta:author: Felix Effenberger trapped: False meta:creation-date: 2023-09-04T10:34:53Z pdf:docinfo:custom:CrossmarkMajorVersionDate: 2010-04-23 created: 2023-09-04T10:34:53Z access_permission:extract_for_accessibility: true Creation-Date: 2023-09-04T10:34:53Z pdf:docinfo:custom:CrossMarkDomains[2]: elsevier.com pdf:docinfo:custom:doi: 10.1016/j.neunet.2023.08.021 pdf:docinfo:custom:CrossmarkDomainExclusive: true Author: Felix Effenberger producer: pdfTeX CrossmarkDomainExclusive: true pdf:docinfo:producer: pdfTeX doi: 10.1016/j.neunet.2023.08.021 pdf:unmappedUnicodeCharsPerPage: 0 dc:description: Neural Networks, 167 (2023) 400-414. doi:10.1016/j.neunet.2023.08.021 access_permission:modify_annotations: true dc:creator: Felix Effenberger description: Neural Networks, 167 (2023) 400-414. doi:10.1016/j.neunet.2023.08.021 dcterms:created: 2023-09-04T10:34:53Z Last-Modified: 2023-09-21T13:30:55Z dcterms:modified: 2023-09-21T13:30:55Z title: A novel feature-scrambling approach reveals the capacity of convolutional neural networks to learn spatial relations xmpMM:DocumentID: uuid:074ab9c7-d5ad-4ae5-ab11-0d324265cf18 Last-Save-Date: 2023-09-21T13:30:55Z CrossMarkDomains[1]: sciencedirect.com pdf:docinfo:modified: 2023-09-21T13:30:55Z meta:save-date: 2023-09-21T13:30:55Z GTS_PDFA1Version: PDF/A-1b:2005 pdf:docinfo:custom:PTEX.Fullbanner: This is pdfTeX, Version 3.14159265-2.6-1.40.21 (TeX Live 2020) kpathsea version 6.3.2 Content-Type: application/pdf X-Parsed-By: org.apache.tika.parser.DefaultParser creator: Felix Effenberger dc:language: en-US access_permission:assemble_document: true xmpTPg:NPages: 15 pdf:charsPerPage: 4518 access_permission:extract_content: true pdf:docinfo:custom:GTS_PDFA1Version: PDF/A-1b:2005 access_permission:can_print: true pdf:docinfo:trapped: False CrossMarkDomains[2]: elsevier.com access_permission:can_modify: true pdf:docinfo:created: 2023-09-04T10:34:53Z CrossmarkMajorVersionDate: 2010-04-23