date: 2023-11-06T18:43:37Z pdf:PDFVersion: 1.4 pdf:docinfo:title: Semantic segmentation of plant roots from RGB (mini-) rhizotron images?generalisation potential and false positives of established methods and advanced deep-learning models xmp:CreatorTool: Springer access_permission:can_print_degraded: true subject: Plant Methods, https://doi.org/10.1186/s13007-023-01101-2 pdfa:PDFVersion: A-2b xmpMM:History:Action: converted language: EN dc:format: application/pdf; version=1.4 pdf:docinfo:custom:robots: noindex pdf:docinfo:creator_tool: Springer access_permission:fill_in_form: true xmpMM:History:When: 2023-11-04T10:38:30Z pdf:encrypted: false dc:title: Semantic segmentation of plant roots from RGB (mini-) rhizotron images?generalisation potential and false positives of established methods and advanced deep-learning models modified: 2023-11-06T18:43:37Z cp:subject: Plant Methods, https://doi.org/10.1186/s13007-023-01101-2 xmpMM:History:SoftwareAgent: pdfToolbox pdf:docinfo:custom:CrossMarkDomains[1]: springer.com robots: noindex pdf:docinfo:subject: Plant Methods, https://doi.org/10.1186/s13007-023-01101-2 xmpMM:History:InstanceID: uuid:a53dbaa6-8fcd-4da5-aaa1-8a8c65ae51b5 pdf:docinfo:creator: Pavel Baykalov meta:author: Bart Bussmann trapped: False meta:creation-date: 2023-11-04T05:07:53Z pdf:docinfo:custom:CrossmarkMajorVersionDate: 2010-04-23 created: 2023-11-04T05:07:53Z access_permission:extract_for_accessibility: true Creation-Date: 2023-11-04T05:07:53Z pdfaid:part: 2 pdf:docinfo:custom:CrossMarkDomains[2]: springerlink.com pdf:docinfo:custom:doi: 10.1186/s13007-023-01101-2 pdf:docinfo:custom:CrossmarkDomainExclusive: true Author: Bart Bussmann producer: Acrobat Distiller 10.1.8 (Windows); modified using iText® 5.3.5 ©2000-2012 1T3XT BVBA (SPRINGER SBM; licensed version) CrossmarkDomainExclusive: true pdf:docinfo:producer: Acrobat Distiller 10.1.8 (Windows); modified using iText® 5.3.5 ©2000-2012 1T3XT BVBA (SPRINGER SBM; licensed version) doi: 10.1186/s13007-023-01101-2 pdf:unmappedUnicodeCharsPerPage: 0 dc:description: Plant Methods, https://doi.org/10.1186/s13007-023-01101-2 Keywords: Automatic image segmentation; Data augmentation; Deep learning; False positives; Fine roots; Image processing; Minirhizotron; Neural networks; Root segmentation; U-Net access_permission:modify_annotations: true dc:creator: Bart Bussmann description: Plant Methods, https://doi.org/10.1186/s13007-023-01101-2 dcterms:created: 2023-11-04T05:07:53Z Last-Modified: 2023-11-06T18:43:37Z dcterms:modified: 2023-11-06T18:43:37Z title: Semantic segmentation of plant roots from RGB (mini-) rhizotron images?generalisation potential and false positives of established methods and advanced deep-learning models xmpMM:DocumentID: uuid:a53dbaa6-8fcd-4da5-aaa1-8a8c65ae51b5 Last-Save-Date: 2023-11-06T18:43:37Z CrossMarkDomains[1]: springer.com pdf:docinfo:keywords: Automatic image segmentation; Data augmentation; Deep learning; False positives; Fine roots; Image processing; Minirhizotron; Neural networks; Root segmentation; U-Net pdf:docinfo:modified: 2023-11-06T18:43:37Z meta:save-date: 2023-11-06T18:43:37Z Content-Type: application/pdf X-Parsed-By: org.apache.tika.parser.DefaultParser creator: Bart Bussmann pdfaid:conformance: B dc:language: EN dc:subject: Automatic image segmentation; Data augmentation; Deep learning; False positives; Fine roots; Image processing; Minirhizotron; Neural networks; Root segmentation; U-Net access_permission:assemble_document: true xmpTPg:NPages: 15 pdf:charsPerPage: 3565 access_permission:extract_content: true access_permission:can_print: true pdf:docinfo:trapped: False CrossMarkDomains[2]: springerlink.com meta:keyword: Automatic image segmentation; Data augmentation; Deep learning; False positives; Fine roots; Image processing; Minirhizotron; Neural networks; Root segmentation; U-Net access_permission:can_modify: true pdf:docinfo:created: 2023-11-04T05:07:53Z CrossmarkMajorVersionDate: 2010-04-23