[1]LIANG Hui,CAO Feng,QIAN Yuhua,et al.Number sequence logic learning in image context[J].CAAI Transactions on Intelligent Systems,2019,14(6):1189-1198.[doi:10.11992/tis.201905044]
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CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
14
Number of periods:
2019 6
Page number:
1189-1198
Column:
学术论文—知识工程
Public date:
2019-11-05
- Title:
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Number sequence logic learning in image context
- Author(s):
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LIANG Hui1; 3; CAO Feng1; 3; QIAN Yuhua1; 2; 3; GUO Qian1; 3; LIANG Xinyan1; 3
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1. Research Institute of Big Data Science and Industry, Shanxi University, Taiyuan 030006, China;
2. Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan 030006, China;
3. School of Computer and Information Technology, Shanxi University, Taiyuan 030006, China
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- Keywords:
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artificial intelligence; logical reasoning; logical learning; deep learning; number sequences; image processing; neural network; pattern construction
- CLC:
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TP181
- DOI:
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10.11992/tis.201905044
- Abstract:
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To solve the problem of pattern construction of unknown numbers and rules, in this paper, we provide a method to solve the problems of number sequence logic learning from the image perspective. The method allows the computer to automatically learn the inherent logic pattern without prior knowledge of the meaning of the image content or of the relationship between images so as to predict the number sequence. Four large datasets were constructed: linear sequences, multiplication sequences, fio sequences, and nested sequences, and then several representative deep neural networks were used to complete the number sequence logic learning task. By analyzing the experimental results, the method was found capable of solving the problem of pattern construction for unknown numbers and rules to a certain extent, which will provide a potential solution for a series of unknown logic pattern construction tasks.