The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
In this paper, a motion retrieval system is investigated from a multiple-instance learning view. To retrieve similar motion data, each human joint's motion clip is regarded as a bag, while each of its segments is regarded as an instance. First 3D temporal- spatial features and their keyspaces of each human joint are extracted. Then, data driven decision trees based on ensemble multiple instance are automatically constructed to reflect the influence of each point during the comparison of motion similarity. Last, we use the method of multiple instance retrieval to complete motion retrieval. Experiment results show that our approaches are effective for motion data retrieval in agriculture inforinatisation.
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