This paper proposes a multistate document segmentation method based on wavelet transform and the hidden Markov tree (HMT) model.
该文基于小波域多状态隐马尔科夫树(HMT)型,引入一种新的文本分割方法。
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The average precision (at IoU of 0.75) and the average recall of instance segmentation reached 0.947 and 0.929 respectively, and the best precision and recall of picking-point detection reached 0.984 and 0.908 respectively.
实例分割的平均精度(在交并比IoU为0.75时)和平均召回率分别达到0.947和0.929,而采摘点检测的最佳精度和召回率则分别达到0.984和0.908。