Robots using Machine Vision in Agriculture
Among the many tasks performed by robots in agriculture, a large part is activated by machine vision algorithms. A very partial list of these tasks would include fields plowing, seeds planting, weeds handling, monitoring of produce growth (be it via ground-based robots or by flying robotic UAVs), fruits and vegetables picking, as well as sorting and grading of produce. This article gives a panoramic view of what our algorithms for robotics can do for your project in agriculture, including robots using Deep Learning in agriculture.
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Image processing for Precision Agriculture
Precision agriculture describes a collection of engineering methods aimed at providing a rationale and operative management plan for farms, forests, vineyards, and other agricultural endeavors,
Grading and sorting
RSIP Vision develops advanced deep learning software for fast and accurate grading and sorting of agricultural produce. One of the key benefits of this solution is its ability to effectively detect existing features and defects, to predict which items will last longer (and therefore can be shipped far away) and which items should be retained for the local market. Sorting and grading machines based on deep learning yield a consistent performance. They are the state-of-the-art solution we recommend today for applications of this kind.
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Date sorting
RSIP Vision has successfully worked in number of dates grading (or dates sorting) projects for our clients. Our automatic fruit recognition system is able to identify with high speed and accuracy all meaningful product features such as size, weight, defect, quality, color, texture, ripeness and others, offering key benefits to our clients: namely, fast and high-volume classification, savings in labor costs, consistent quality and reduced time-to-market.
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