Abstract
Deep learning computer vision research has been widely used agriculture field to reduce labor costs and provide technical support for fruit farmers. At present, most object detection algorithms cannot effectively extend to the mountain orchard scene. This paper designs a fast and efficient citrus detection system, which combines unmanned aerial photography and edge computing device. The system uses low altitude UAV to take an omnidirectional image of citrus at different angles. Then, we optimize the state-of-the-art object detection model, use the attention mechanism to enhance the detection effect of small citrus objects. We use UAV to collect citrus fruit images and use the improved model for detection. The experimental results show that the detection accuracy of the model for citrus fruit data set is 93.42%. The detection time of single citrus fruit image in the edge device is 310 ms.
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Huang, H., Kadoch, M. (2022). Portable Citrus Detection System Combining UAV and Edge Equipment. In: Sun, S., Hong, T., Yu, P., Zou, J. (eds) Signal and Information Processing, Networking and Computers. ICSINC 2021. Lecture Notes in Electrical Engineering, vol 895. Springer, Singapore. https://doi.org/10.1007/978-981-19-4775-9_49
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DOI: https://doi.org/10.1007/978-981-19-4775-9_49
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