Home | Computer Engineering and Informatics Department - Laboratory for Pattern Recognition
Computer Engineering and Informatics Department - Laboratory for Pattern Recognition
Computer Engineering and Informatics Department - Laboratory for Pattern Recognition University of Patras
Organisation type:
Research institutions
University
ICT provider
Country:
Greece
Short name:
UP
Description:
The University of Patras will participate in the project with two departments. The Department of Business Administration of Food and Agricultural Enterprises, the Department of Computer Engineering and Computer Science (Pattern Recognition Laboratory) which have an important knowledge in the area of agribusiness, combining knowledge in economics, management and agriculture and extensive experience in the Internet of Things, Artificial Intelligence, Decision Support Systems, Deep Learning and ICT in Precision Agriculture. They also have experience in large data management, use of new technologies, digitization, long-term digital archiving and information systems, internet and Web 2.0 services.” The University will use infrastructure already installed for big food data management and precision agriculture as well as already developed algorithms for large volume data analysis, cloud computing based on the open source CloudStack platforms and artificial intelligence tools for decision support systems in agri-food production.
Computer Engineering and Informatics Department - Laboratory for Pattern Recognition
University of Patras
The University of Patras will participate in the project with two departments. The Department of Business Administration of Food and Agricultural Enterprises, the Department of Computer Engineering and Computer Science (Pattern Recognition Laboratory) which have an important knowledge in the area of agribusiness, combining knowledge in economics, management and agriculture and extensive experience in the Internet of Things, Artificial Intelligence, Decision Support Systems, Deep Learning and ICT in Precision Agriculture. They also have experience in large data management, use of new technologies, digitization, long-term digital archiving and information systems, internet and Web 2.0 services.” The University will use infrastructure already installed for big food data management and precision agriculture as well as already developed algorithms for large volume data analysis, cloud computing based on the open source CloudStack platforms and artificial intelligence tools for decision support systems in agri-food production.