Keyword automatic recognition and annotation algorithms have important value in automatic analysis and machine recognition understanding of alcoholic history literature.Firstly,the YOLOv7 network model is used for text box recognition in liquor literature.Secondly the CBAM attention mechanism is introduced to obtain features such as text box position and size.Thirdly,the PaddleOCR algorithm is used to achieve keyword recognition in liquor literature.Finally,text repair technology is applied for optimization processing.The experimental analysis system designed using this detection algorithm can efficiently pro-cess massive alcohol literature data,extract text information related to alcohol with a 90％recognition rate,and effectively over-come the special situation of blurred and incomplete text printing and diverse font types in alcohol literature,achieving good rec-ognition and annotation results in the experiment.
关键词
深度学习/卷积神经网络/文字识别/酒文献
Key words
deep learning/convolutional neural networks/text recognition/wine literature
维普
万方数据