Online Identification Method of Tea Diseases in Complex Natural Environments
نویسندگان
چکیده
An intelligent Internet-of-Things (IoT) hardware system in the field tea plantations was built, comprising collection of images by HD zoom cameras a cluster structure and deployment detection model cluster-head edge computing nodes. Data sent to customer premise equipment through nodes gateways then cloud platforms, which provided platform for identifying remote disease online. Field-placed were used as main acquisition means study various diseases on Yashixiang, typical variety Chaozhou Dancong tea, different seasons weather conditions shooting angles natural year period with complex backgrounds. In turn, we constructed environment high-quality dataset covering major e.g., anthracnose, leaf blight, grey Pseudocercospora theae, etc. explored feasibility deep learning algorithms automatic identification diseases. Results showed that recognition rate Swim Transformer reached 94% environments. This paper demonstrated effectiveness applied laying foundation practical application technology
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ژورنال
عنوان ژورنال: IEEE open journal of the Computer Society
سال: 2023
ISSN: ['2644-1268']
DOI: https://doi.org/10.1109/ojcs.2023.3247505