Mapping poverty data integration par asian development (31 résultats)

Etat : New.

Paperback or Softback. Etat : New. Mapping Poverty through Data Integration and Artificial Intelligence: A Special Supplement of the Key Indicators for Asia and the Pacific. Book.

Etat : As New. Unread book in perfect condition.

Etat : New.

Paperback. Etat : New. This special supplement to the Key Indicators for Asia and the Pacific 2020 discusses how poverty estimates can be enhanced by integrating household surveys and censuses with data extracted from satellite imagery. As part of a special ADB knowledge initiative, computer vision techniques and machine-learning algorithms were applied on datasets from the Philippines and Thailand to demonstrate increased granularity of poverty estimation using artificial intelligence. The report identifies practical considerations and technical requirements for this novel approach to mapping the spatial distribution of poverty. It also outlines the investments required by national statistics offices to fully capitalize on the benefits of incorporating innovative data sources into conventional work programs.…

Etat : New. In English.

Etat : New.

Etat : As New. Unread book in perfect condition.

Etat : New.

Paperback or Softback. Etat : New. A Guidebook on Mapping Poverty through Data Integration and Artificial Intelligence. Book.

Etat : New.

Etat : As New. Unread book in perfect condition.

Paperback. Etat : New. This guidebook identifies tools and resources that can help generate poverty statistics using satellite imagery, geospatial data, and machine-learning algorithms to augment conventional data collection and sample survey techniques.The "leave no one behind" principle of the 2030 Agenda for Sustainable Development requires appropriate indicators to be estimated for different segments of a country's population. The guidebook was based on a feasibility study by ADB, in collaboration with the Philippine Statistics Authority, the National Statistical Office of Thailand, and the World Data Lab, that aimed to enhance the granularity, cost-effectiveness, and compilation of high-quality poverty statistics. It also serves as an accompanying guide to the Key Indicators for Asia and the Pacific 2020 special supplement focusing on mapping poverty estimates.…

Etat : New.

Etat : New. In English.

Etat : As New. Unread book in perfect condition.

Paperback. Etat : New. This special supplement to the Key Indicators for Asia and the Pacific 2020 discusses how poverty estimates can be enhanced by integrating household surveys and censuses with data extracted from satellite imagery. As part of a special ADB knowledge initiative, computer vision techniques and machine-learning algorithms were applied on datasets from the Philippines and Thailand to demonstrate increased granularity of poverty estimation using artificial intelligence. The report identifies practical considerations and technical requirements for this novel approach to mapping the spatial distribution of poverty. It also outlines the investments required by national statistics offices to fully capitalize on the benefits of incorporating innovative data sources into conventional work programs.…

Paperback. Etat : New. This guidebook identifies tools and resources that can help generate poverty statistics using satellite imagery, geospatial data, and machine-learning algorithms to augment conventional data collection and sample survey techniques.The "leave no one behind" principle of the 2030 Agenda for Sustainable Development requires appropriate indicators to be estimated for different segments of a country's population. The guidebook was based on a feasibility study by ADB, in collaboration with the Philippine Statistics Authority, the National Statistical Office of Thailand, and the World Data Lab, that aimed to enhance the granularity, cost-effectiveness, and compilation of high-quality poverty statistics. It also serves as an accompanying guide to the Key Indicators for Asia and the Pacific 2020 special supplement focusing on mapping poverty estimates.…

paperback. Etat : New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

PAP. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Etat : New. Print on Demand pp. 54.

Etat : New. Print on Demand pp. 54.

Etat : New. PRINT ON DEMAND pp. 54.

PAP. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Etat : New. Print on Demand pp. 274.

Etat : New. Print on Demand pp. 274.

Etat : New. PRINT ON DEMAND pp. 274.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This special supplement to the Key Indicators for Asia and the Pacific 2020 discusses how poverty estimates can be enhanced by integrating household surveys and censuses with data extracted from satellite imagery. As part of a special ADB knowledge initiative, computer vision techniques and machine-learning algorithms were applied on datasets from the Philippines and Thailand to demonstrate increased granularity of poverty estimation using artificial intelligence. The report identifies practical considerations and technical requirements for this novel approach to mapping the spatial distribution of poverty. It also outlines the investments required by national statistics offices to fully capitalize on the benefits of incorporating innovative data sources into conventional work programs.…

Taschenbuch. Etat : Neu. Mapping Poverty through Data Integration and Artificial Intelligence | A Special Supplement of the Key Indicators for Asia and the Pacific | Asian Development Bank | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2021 | Asian Development Bank | EAN 9789292623135 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This guidebook identifies tools and resources that can help generate poverty statistics using satellite imagery, geospatial data, and machine-learning algorithms to augment conventional data collection and sample survey techniques.The 'leave no one behind' principle of the 2030 Agenda for Sustainable Development requires appropriate indicators to be estimated for different segments of a country's population. The guidebook was based on a feasibility study by ADB, in collaboration with the Philippine Statistics Authority, the National Statistical Office of Thailand, and the World Data Lab, that aimed to enhance the granularity, cost-effectiveness, and compilation of high-quality poverty statistics. It also serves as an accompanying guide to the Key Indicators for Asia and the Pacific 2020 special supplement focusing on mapping poverty estimates.…