Search results for RFI
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49 datasets for “RFI”
- GovData Germany
Entwurf eines Staatsvertrages zur Reform des Verfahrens zur Festsetzung des Rundfunkbeitrages (Rundfunkfinanzierungsänderungsstaatsvertrag)
Land Rheinland-PfalzUpdated 12 Nov 2026
Der Beschluss dient der Einleitung des Vorunterrichtungsverfahrens beim Landtag, um den Ministerpräsidenten zu ermächtigen, den „Staatsvertrag zur Reform …
- Data.gov Catalog
Radio Frequency Interference Measurements of Industrial Machinery
National Institute of Standards and TechnologyUpdated 14 Feb 2025
… General recording of the 2400 MHz band capturing both wireless network traffic and an unidentified broadband RFI emitter …
- PNG
- PLAIN
- X-OBJCSRC
- CSV
- X-MATLAB-DATA
- +1
- data.gouv.fr
SOCIETE D'ANIMATION ET DE GESTION
SNEEUpdated 13 Oct 2023
Fourniture de 2 bornes piédestal RFID : - 1 Borne 2X7.4KW - 1 Borne 2X22KW
- XLSX
- CSV
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 16 Oct 2025
… Of the 18 compared methods, RFIDS and RFOK are the most accurate methods in all three regions. Overall …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 20 Jan 2026
… Of the 18 compared methods, RFIDS and RFOK are the most accurate methods in all three regions. Overall …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 2 Mar 2026
… Of the 18 compared methods, RFIDS and RFOK are the most accurate methods in all three regions. Overall …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 7 Mar 2026
… Of the 18 compared methods, RFIDS and RFOK are the most accurate methods in all three regions. Overall …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 25 Mar 2026
… Of the 18 compared methods, RFIDS and RFOK are the most accurate methods in all three regions. Overall …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 20 Apr 2026
… Of the 18 compared methods, RFIDS and RFOK are the most accurate methods in all three regions. Overall …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 30 Apr 2026
… Of the 18 compared methods, RFIDS and RFOK are the most accurate methods in all three regions. Overall …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Australian Ocean Data NetworkUpdated 11 Jan 2026
… Of the 18 compared methods, RFIDS and RFOK are the most accurate methods in all three regions. Overall …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Australian Ocean Data NetworkUpdated 23 Jan 2026
… Of the 18 compared methods, RFIDS and RFOK are the most accurate methods in all three regions. Overall …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Australian Ocean Data NetworkUpdated 12 Feb 2026
… Of the 18 compared methods, RFIDS and RFOK are the most accurate methods in all three regions. Overall …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Australian Ocean Data NetworkUpdated 5 Mar 2026
… Of the 18 compared methods, RFIDS and RFOK are the most accurate methods in all three regions. Overall …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Australian Ocean Data NetworkUpdated 16 Mar 2026
… Of the 18 compared methods, RFIDS and RFOK are the most accurate methods in all three regions. Overall …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Australian Ocean Data NetworkUpdated 29 Mar 2026
… Of the 18 compared methods, RFIDS and RFOK are the most accurate methods in all three regions. Overall …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Australian Ocean Data NetworkUpdated 4 Apr 2026
… Of the 18 compared methods, RFIDS and RFOK are the most accurate methods in all three regions. Overall …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Australian Ocean Data NetworkUpdated 10 Apr 2026
… Of the 18 compared methods, RFIDS and RFOK are the most accurate methods in all three regions. Overall …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Australian Ocean Data NetworkUpdated 16 Apr 2026
… Of the 18 compared methods, RFIDS and RFOK are the most accurate methods in all three regions. Overall …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Australian Ocean Data NetworkUpdated 28 Apr 2026
… Of the 18 compared methods, RFIDS and RFOK are the most accurate methods in all three regions. Overall …
- HTML