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
With the rapid development of modern information technology, target recognition plays an increasingly important role in agricultural production, national defense construction. However, the existing target recognition algorithm has many limitations, such as image distortion, difficult to recognize target image or poor recognition results because of camera angles and lighting conditions. Based on the above questions, the paper proposes an image recognition algorithm, and the light field is applied to the image recognition as the feature extraction library for first time. First, we obtain light field information which contains images taken from different angles of the target object, and then regard the light field information as an object library. Finally we perform the algorithm of target recognition for the target image based on the object library. Based on sparse Fourier transform, the light field reconstruction algorithm in this paper can reconstruct the entire light field with a small amount of samples. This recognition algorithm can solve the problem to recognize image due to the different camera angles. Finally, the simulation verifies the effectiveness of the algorithm.
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