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<p class="MsoBodyText"><span lang="EN-GB">Within the context of training data for Earth Observation (EO) Artificial Intelligence Machine Learning (AI/ML), this document specifies a conceptual model that:</span></p>
<p class="ListContinue1" style="mso-list: l0 level1 lfo1;"><!-- [if !supportLists]--><span lang="EN-GB" style="mso-fareast-font-family: Cambria; mso-bidi-font-family: Cambria;"><span style="mso-list: Ignore;">—<span style="font: 7.0pt 'Times New Roman';"> </span></span></span><!--[endif]--><span lang="EN-GB">establishes a UML model with a target of maximizing the interoperability and usability of EO imagery training data;</span></p>
<p class="ListContinue1" style="mso-list: l0 level1 lfo1;"><!-- [if !supportLists]--><span lang="EN-GB" style="mso-fareast-font-family: Cambria; mso-bidi-font-family: Cambria;"><span style="mso-list: Ignore;">—<span style="font: 7.0pt 'Times New Roman';"> </span></span></span><!--[endif]--><span lang="EN-GB">specifies different AI/ML tasks and labels in EO in terms of supervised learning, including scene level, object level and pixel level tasks;</span></p>
<p class="ListContinue1" style="mso-list: l0 level1 lfo1;"><!-- [if !supportLists]--><span lang="EN-GB" style="mso-fareast-font-family: Cambria; mso-bidi-font-family: Cambria;"><span style="mso-list: Ignore;">—<span style="font: 7.0pt 'Times New Roman';"> </span></span></span><!--[endif]--><span lang="EN-GB">describes the permanent identifier, version, licence, training data size, measurement or imagery used for annotation;</span></p>
<p class="ListContinue1" style="mso-list: l0 level1 lfo1;"><!-- [if !supportLists]--><span lang="EN-GB" style="mso-fareast-font-family: Cambria; mso-bidi-font-family: Cambria;"><span style="mso-list: Ignore;">—<span style="font: 7.0pt 'Times New Roman';"> </span></span></span><!--[endif]--><span lang="EN-GB">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).</span></p>
Reģistrācijas numurs (WIID)
89050
Darbības sfēra
<p class="MsoBodyText"><span lang="EN-GB">Within the context of training data for Earth Observation (EO) Artificial Intelligence Machine Learning (AI/ML), this document specifies a conceptual model that:</span></p>
<p class="ListContinue1" style="mso-list: l0 level1 lfo1;"><!-- [if !supportLists]--><span lang="EN-GB" style="mso-fareast-font-family: Cambria; mso-bidi-font-family: Cambria;"><span style="mso-list: Ignore;">—<span style="font: 7.0pt 'Times New Roman';"> </span></span></span><!--[endif]--><span lang="EN-GB">establishes a UML model with a target of maximizing the interoperability and usability of EO imagery training data;</span></p>
<p class="ListContinue1" style="mso-list: l0 level1 lfo1;"><!-- [if !supportLists]--><span lang="EN-GB" style="mso-fareast-font-family: Cambria; mso-bidi-font-family: Cambria;"><span style="mso-list: Ignore;">—<span style="font: 7.0pt 'Times New Roman';"> </span></span></span><!--[endif]--><span lang="EN-GB">specifies different AI/ML tasks and labels in EO in terms of supervised learning, including scene level, object level and pixel level tasks;</span></p>
<p class="ListContinue1" style="mso-list: l0 level1 lfo1;"><!-- [if !supportLists]--><span lang="EN-GB" style="mso-fareast-font-family: Cambria; mso-bidi-font-family: Cambria;"><span style="mso-list: Ignore;">—<span style="font: 7.0pt 'Times New Roman';"> </span></span></span><!--[endif]--><span lang="EN-GB">describes the permanent identifier, version, licence, training data size, measurement or imagery used for annotation;</span></p>
<p class="ListContinue1" style="mso-list: l0 level1 lfo1;"><!-- [if !supportLists]--><span lang="EN-GB" style="mso-fareast-font-family: Cambria; mso-bidi-font-family: Cambria;"><span style="mso-list: Ignore;">—<span style="font: 7.0pt 'Times New Roman';"> </span></span></span><!--[endif]--><span lang="EN-GB">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).</span></p>
