Mobile QR Code QR CODE

2025

Reject Ratio

81.5%

References

1 
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2 
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3 
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4 
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5 
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6 
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7 
S. Hu , Q. Wang , K. Huang , M. Wen , F. Coenen , Retrieval-based language model adaptation for handwritten Chinese text recognition, International Journal on Document Analysis and Recognition, Vol. 26, No. 2, pp. 109-119, 2023DOI
8 
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9 
X. Ma , H. Xu , X. Zhang , H. Wang , An improved deep learning network structure for multitask text implication translation character recognition, Complexity, Vol. 2021, No. 5, pp. 901-911, 2021DOI
10 
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11 
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12 
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13 
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14 
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15 
M. Jia , L. Shen , X. Shen , L. Liao , M. Chen , X. He , Z. Chen , J. Li , Mner-qg: an end-to-end mrc framework for multimodal named entity recognition with query grounding, Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 37, No. 7, pp. 8032-8040, 2023DOI
16 
Y. Guo , Z. Mustafaoglu , D. Koundal , Spam detection using bidirectional transformers and machine learning classifier algorithms, Journal of Computational and Cognitive Engineering, Vol. 2, No. 1, pp. 5-9, 2023DOI
17 
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18 
B. Gao , Y. Pan , C. Li , S. Geng , H. Zhao , Are we hungry for 3D LiDAR data for semantic segmentation? A survey of datasets and methods, IEEE Transactions on Intelligent Transportation Systems, Vol. 23, No. 7, pp. 6063-6081, 2022DOI
19 
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20 
Sakshi , V. Kukreja , A retrospective study on handwritten mathematical symbols and expressions: classification and recognition, Engineering Applications of Artificial Intelligence, Vol. 103, 2021DOI