Human resource recommendation algorithm based on convolutional neural network
Among various kinds of image recognition, the Chinese character recognition has a very wide range of application prospect and practical value, for example, can be used in sorting, license plate recognition, billboard recognition, identity CARDS, auxiliary blind people read scene, can realize automat...
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| Vydané v: | 2023 IEEE International Conference on Control, Electronics and Computer Technology (ICCECT) s. 1343 - 1348 |
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| Hlavní autori: | , , |
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| Jazyk: | English |
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IEEE
28.04.2023
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| Abstract | Among various kinds of image recognition, the Chinese character recognition has a very wide range of application prospect and practical value, for example, can be used in sorting, license plate recognition, billboard recognition, identity CARDS, auxiliary blind people read scene, can realize automatic recognition, reduce artificial operation, save time and manpower cost, convenient people's life. Deep learning mainly builds a neural network model with multiple hidden layers. In this paper, a large number of training samples are used to learn more useful features, so as to improve the prediction and classification accuracy of the network model. As an important network model of deep learning, convolutional neural network has the characteristics of hierarchical structure, weight sharing, regional local perception, feature extraction and global training combined with classification process, etc., and has been widely applied in the field of image recognition. In particular, deep convolutional neural network is currently a research hotspot. It is of great application value to study its own and its application in the identification of different samples. |
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| AbstractList | Among various kinds of image recognition, the Chinese character recognition has a very wide range of application prospect and practical value, for example, can be used in sorting, license plate recognition, billboard recognition, identity CARDS, auxiliary blind people read scene, can realize automatic recognition, reduce artificial operation, save time and manpower cost, convenient people's life. Deep learning mainly builds a neural network model with multiple hidden layers. In this paper, a large number of training samples are used to learn more useful features, so as to improve the prediction and classification accuracy of the network model. As an important network model of deep learning, convolutional neural network has the characteristics of hierarchical structure, weight sharing, regional local perception, feature extraction and global training combined with classification process, etc., and has been widely applied in the field of image recognition. In particular, deep convolutional neural network is currently a research hotspot. It is of great application value to study its own and its application in the identification of different samples. |
| Author | Li, Haoran Liu, Jiakun Wan, Li |
| Author_xml | – sequence: 1 givenname: Jiakun surname: Liu fullname: Liu, Jiakun email: huachebin83075550@126.com organization: Shandong Youth University of Political Science,Jinan,China,250103 – sequence: 2 givenname: Haoran surname: Li fullname: Li, Haoran organization: Shandong Youth University of Political Science,Jinan,China,250103 – sequence: 3 givenname: Li surname: Wan fullname: Wan, Li organization: Shandong Youth University of Political Science,Jinan,China,250103 |
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| Snippet | Among various kinds of image recognition, the Chinese character recognition has a very wide range of application prospect and practical value, for example, can... |
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| SubjectTerms | Character recognition Convolutional neural network Convolutional neural networks Deep learning Human resources Image recognition Neural networks Predictive models Recommendation algorithm Training |
| Title | Human resource recommendation algorithm based on convolutional neural network |
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