Evaluation of Deep Learning Models for Polymetallic Nodule Detection and Segmentation in Seafloor Im...
Evaluation of Deep Learning Models for Polymetallic Nodule Detection and Segmentation in Seafloor Imagery
About this item
Full title
Author / Creator
Publisher
Basel: MDPI AG
Journal title
Language
English
Formats
Publication information
Publisher
Basel: MDPI AG
Subjects
More information
Scope and Contents
Contents
Climate change has led to the need to transition to clean technologies, which depend on an number of critical metals. These metals, such as nickel, lithium, and manganese, are essential for developing batteries. However, the scarcity of these elements and the risks of disruptions to their supply chain have increased interest in exploiting resources...
Alternative Titles
Full title
Evaluation of Deep Learning Models for Polymetallic Nodule Detection and Segmentation in Seafloor Imagery
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_2c9b8c9ca9a64655961a79d14a0646c9
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_2c9b8c9ca9a64655961a79d14a0646c9
Other Identifiers
ISSN
2077-1312
E-ISSN
2077-1312
DOI
10.3390/jmse13020344
