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Více informací o knize Robust Methods for the Analysis of Images and Videos for Fisheries Stock Assessment

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Anotace knihy

The National Marine Fisheries Service (NMFS) is responsible for the stewardship of the nation's living marine resources and their habitat. As part of this charge, NMFS conducts stock assessments of the abundance and composition of fish stocks in several bodies of water. At present, stock assessments rely heavily on human data-gathering and analysis. Automatic means of fish stock assessments are appealing because they offer the potential to improve efficiency and reduce human workload and perhaps develop higher-fidelity measurements. The use of images and video, when accompanies by appropriate statistical analyses of the inferred data, is of increasing importance for estimating the abundance of species and their age distributions. Robust Methods for the Analysis of Images and Videos for Fisheries Stock Assessment is the summary of a workshop convened by the National Research Council Committee on Applied and Theoretical Statistics to discuss analysis techniques for images and videos for fisheries stock assessment. Experts from diverse communities shared perspective about the most efficient path toward improved automation of visual information and discussed both near-term and long-term goals that can be achieved through research and development efforts. This report is a record of the presentations and discussions of this event.

Parametry knihy

Zařazení knihy Knihy v angličtině Mathematics & science Mathematics

• Plný název: Robust Methods for the Analysis of Images and Videos for Fisheries Stock Assessment
• Podnázev: Summary of a Workshop
• Autor: Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Their Applications, Division on Engineering and Physical Sciences,
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 66
• EAN: 9780309314695
• ID: 09104330
• Nakladatelství: National Academies Press
• Hmotnost: 181 g
• Rozměry: 254 × 178 × 8 mm
• Datum vydání: 31. December 2014

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