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COMPUTER VISION-BASED YIELD-TO-PICKING AREA MAPPING FOR HORTICULTURAL PRODUCT

机译:基于计算机视觉的园艺产品的促进区域测绘

摘要

Embodiments of the disclosed technologies are capable of inputting, to a machine-learned model that has been trained to recognize a horticultural product in digital imagery, digital video data comprising frames that represent a view of the horticultural product in belt-assisted transit from a picking area of a field to a harvester bin; outputting, by the machine-learned model, annotated video data; using the annotated video data, computing quantitative data comprising particular counts of the individual instances of the horticultural product associated with particular timestamp data; using the timestamp data, mapping the quantitative data to geographic location data to produce a digital yield map; causing display of the digital yield map on a field manager computing device.
机译:所公开的技术的实施例能够输入到已经训练以识别数字图像中识别园艺产品的机器学习模型,该数字视频数据包括代表从拣选中的皮带辅助运输中的园艺产品视图的帧。 一个领域的地区到收割机垃圾箱; 通过机器学习模型输出,注释视频数据; 使用注释的视频数据,计算包括与特定时间戳数据相关的园艺产品的各个实例的特定计数的定量数据; 使用时间戳数据,将定量数据映射到地理位置数据以产生数字产量图; 导致现场管理器计算设备上的数字屈服映射的显示。

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