本发明提供用于获得高精密度的对待利用于学习神经网络的训练图像进行自动标注(auto‑labeling)的方法，包括：步骤(a)，自动标注装置使元感兴趣区域(ROI，Region Of Interest)检测网络输出特征地图，获得特定训练图像上的对象根据各个位置进行分组的n个当前元感兴趣区域；以及步骤(b)，自动标注装置通过在特定训练图像上对与n个当前元感兴趣区域相对应的区域进行裁剪(crop)来生成n个加工图像，使对象检测网络分别输出具有分别与n个加工图像有关的各个边界框的n个所自动标注的加工图像，通过合并n个所自动标注的加工图像来生成所自动标注的特定训练图像。方法可利用使用策略梯度算法(policy gradient algorithm)的强化学习、在线学习、连续学习及超参数学习来执行。
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[ DB ] CONNECT:[ UseTime:0.001306s ] mysql:host=pc-m5epcw1px949b110u.rwlb.rds.aliyuncs.com;port=3306;dbname=yousedb;charset=utf8
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[ SQL ] SHOW COLUMNS FROM `tb_industry_report` [ RunTime:0.001143s ]
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