Ellips & Elisam Utilize Deep Learning to Take Fruit Grading Technology to the Next Level
Not only has this system improved the defect grading capabilities, also the capacity of the machine increased significantly. The Elisam GranTorino sorting machine could now easily process 1000 kg/h per lane.
Some Deep Learnings from Applying Deep Learning
To build a robust deep learning model, it can be much more than training or fine tuning some existing models (e.g. inception v3, resnet, LSTM, etc.) with your own dataset. These winning models are your best friend and can usually serve as base models.
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How to overcome GNSS limitations with RTK correction services
Although GNSS offers ubiquitous coverage worldwide, its accuracy can be hindered in some situations - signals can be attenuated by heavy vegetation, for example, or obstructed by tall buildings in dense urban canyons. This results in signals being received indirectly or via the multipath effect, leading to inaccuracy, or even blocked entirely. Unimpeded GNSS positioning in all real world scenarios is therefore unrealistic - creating a need for supporting technologies, such as real time kinematic (RTK) positioning and dead reckoning, to enable centimeter-accuracy for newer mass-market IoT devices.
