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基于关键词指导的图像中文描述生成 

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[17] Ren, Z., Wang, X., Zhang, N., Lv, X. and Li, L.J. (2017) Deep Reinforcement Learning-Based Image Captioning with

Embedding Reward. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, 21-26 July 2017, 290-298. https://doi.org/10.1109/CVPR.2017.128 [18] Zhang, L., Sung, F., Liu, F., Xiang, T., Gong, S., Yang, Y. and Hospedales, T.M. (2017) Actor-Critic Sequence Train-ing for Image Captioning. arXiv preprint arXiv:1706.09601 [19] Simonyan, K. and Zisserman, A. (2014) Very Deep Convolutional Networks for Large-Scale Image Recognition. ar-Xiv preprint arXiv:1409.1556 [20] Hochreiter, S. and Schmidhuber, J. (1997) Long Short-Term Memory. Neural Computation, 9, 1735-1780.

https://doi.org/10.1162/neco.1997.9.8.1735

[21] Papineni, K., Roukos, S., Ward, T. and Zhu, W.J. (2002) BLEU: A Method for Automatic Evaluation of Machine

Translation. Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, July 2002, 311-318. https://doi.org/10.3115/1073083.1073135 [22] Lin, C.Y. and Och, F.J. (2004) Looking for a Few Good Metrics: ROUGE and Its Evaluation. NTCIR Workshop,

Tokyo, 2-4 June 2004. [23] Vedantam, R., Lawrence Zitnick, C. and Parikh, D. (2015) Cider: Consensus-Based Image Description Evaluation.

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Boston, MA, 7-12 June 2015, 4566-4575. https://doi.org/10.1109/CVPR.2015.7299087 [24] Sun, J. (2012) Jieba Chinese Word Segmentation Tool. https://github.com/fxsjy/jieba

[25] Deng, J., Dong, W., Socher, R., Li, L.J., Li, K. and Li, F.-F. (2009) ImageNet: A Large-Scale Hierarchical Image Da-tabase. 2009 IEEE Conference on Computer Vision and Pattern Recognition, Miami, FL, 20-25 June 2009, 248-255. https://doi.org/10.1109/CVPR.2009.5206848 [26] Ling, W., Dyer, C., Black, A.W. and Trancoso, I. (2015) Two/Too Simple Adaptations of Word2Vec for Syntax Prob-lems. Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Lin-guistics: Human Language Technologies, Denver, Co, May-June 2015, 1299-1304. https://doi.org/10.3115/v1/N15-1142 [27] gensim: Topic Modelling for Humans. Radimrehurek.com. https://radimrehurek.com/gensim/models/word2vec.html

DOI: 10.12677/csa.2020.106113

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计算机科学与应用

基于关键词指导的图像中文描述生成 

史秀聪[17]Ren,Z.,Wang,X.,Zhang,N.,Lv,X.andLi,L.J.(2017)DeepReinforcementLearning-BasedImageCaptioningwithEmbeddingReward.ProceedingsoftheIEEEConference
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