e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

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.

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An assistant for an incremental learning based image processing system


Supervised learning has been applied in image processing system for object recognition, inspection and measurement. However the teaching-learning mode of supervised learning is not practical in real application, because it is impossible to teach a system all possible samples in one time. Therefore, incremental learning is considered to be a promising solution which supports the iteration of teaching-learning in cycles. An incremental learning based system can always be taught and can learn new samples of objects. However, from engineering perspective, incremental learning is not so practical for user in a teaching-learning cycle. For this reason, an assistant is proposed to support teaching-learning cycles. The assistant includes the following four functions: "result monitoring", "auxiliary teaching", "incremental learning" and "classifier evaluation". With the help of an assistant, system user is able to control the whole teaching-learning cycle, and interact with the image processing system easily. The concept of an assistant is tested by experiments of classifying agricultural products. It is proved that the assistant is a practical manner in image processing system.

  • DE
  • Univ_Stuttgart (DE)
Data keywords
  • machine learning
Agriculture keywords
  • agriculture
Data topic
  • big data
  • modeling
Document type

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Institutions 10 co-publis
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    e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
    Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.