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Imaging · dataset · 2022

U_Net_Ni_WC_Optical_images

Listed in Teesside University Research Data Repository

This data was used to train a U-Net convolutional neural network to semantically segment WC from Ni-WC optical microscopy images.

Description

The training and test datasets contain 194 and 37 512x512 pixel images and their corresponding ground truths, respectively.

Links

Where it is published

Catalogue records · 1

Topics

From keywords
Computer Science & AI · Computer vision · Earth & Environmental Science · Microscopy
Inferred from text
Image 65%
Provenance · 1 source records, 10 field assertions
SourceKeyLast seenRaw
Teesside University Research Data Repositoryoai:data.mendeley.com/2wmbc95xy9.119 h agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].anzsrc:field:460304mapping · researchdata tees ac ukvocabulary-mapper@1.0.0keywords['Computer Vision']
concepts[field].local:field:computer-science-aimapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].local:field:earth-environmentalmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[modality].local:modality:imageenrichment · researchdata tees ac ukkeyword-concept-rules@1.0.0title+description (65%)
concepts[modality].local:modality:microscopymapping · researchdata tees ac ukvocabulary-mapper@1.0.0keywords['Light Microscopy']
descriptionsource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/description
licensesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/rights
publication_datesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
titlesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/title