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| Filter results2 paper(s) found. |
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1. Just a moment; the need for streamlining precision agriculture data in AfricaPrecision agriculture (PA) data sources in the era of digital agriculture are diverse in terms of the range of technology options and the types of data they generate. These include proximal sensors, unmanned aerial vehicle (UAV), satellites, farm machinery mounted sensors and robotics to generate static data or real time information (e.g., yield monitoring). Government institutions, scientists and private sectors take the lion’s share in generating PA data at innovation, validation and dissemination... T.B. Gobezie, A. Biswas |
2. LiDAR-based soybean crop segmentation for autonomous navigationThe technological advances in the last few decades have greatly changed agricultural operations. In order to became safer, more profitable, efficient, and sustainable, modern farms have adopted the use of sophisticated technologies, such as robots, sensors, aerial images, and GNSS (Global Navigation Satellite System). These technologies not only increase the crop productivity, but also reduce the wide use of water, fertilisers, and pesticides. Due to this, they reduce costs and negative environmental... V.A. Higuti, A.E. Velasquez, M.V. Gasparino, D.V. Magalhães, M. Becker, D.M. Milori, R.V. Aroca |