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Using Deep Learning Method to Conduct Paddy Field Detection and Staging in Aerial Images in Geographic Information System
This study primarily employs ArcGIS Pro, a geographic information software, to accomplish the task of developing a deep learning model. It utilizes the stage-wise classification of rice growth to train the Mask RCNN instance segmentation model, which enables the identification of paddy fields in various phenological stages and the production of corresponding rice field maps.
AIoT System for Facility Asparagus Cultivation
Chou, C., Chang, S., Zhong, Z., Guo, M., Hsieh, M., Peng, J., Tai, ling-chieh, Chung, P., Wang, J., & Jiang, J. (2023). Development of AIoT System for Facility Asparagus Cultivation. Computers and Electronics in Agriculture, 206(107665), 0168–1699.
Optimizing the growth of asparagus in the facility through the results of asparagus pest counts and environment data
Applying Deep Learning to Monitoring Honey Bees Entering and
Leaving the Nest
Establish pollination efficiency evaluation indicators by tracking and counting honeybees entering and leaving the nest and identifying the area of pollen grains
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