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Geographic information. Training data markup language for artificial intelligence. Conceptual model | Status: Current
description
1 Scope
Within the context of training data for Earth Observation (EO) Artificial IntelligenceMachine Learning (AI/ML), this document specifies a conceptual model that:
- — establishes a UML model with a target of maximizing the interoperability and usability of EO imagery training data;
- — specifies different AI/ML tasks and labels in EO in terms of supervised learning, including scene level, object level and pixel level tasks;
- — describes the permanent identifier, version, licence, training data size, measurement or imagery used for annotation;
- — specifies a description of quality (e.g. training data errors, training data representativeness, quality measures) and provenance (e.g. agents who perform the labelling, labelling procedure).
Details
Publisher
BS
File size
2.76 MB
Pages
58
Format
PDF
Publication date
2025-06-06
ISBN-13
978-0-539-30629-3
ISBN-13 plain
9780539306293
ISBN-10
0539306293
