| Challenges in representation learning: A report on three machine learning contests IJ Goodfellow, D Erhan, PL Carrier, A Courville, M Mirza, B Hamner, ... Neural information processing: 20th international conference, ICONIP 2013 …, 2013 | 2301 | 2013 |
| Cross-modal retrieval with correspondence autoencoder F Feng, X Wang, R Li Proceedings of the 22nd ACM international conference on Multimedia, 7-16, 2014 | 680 | 2014 |
| Dual graph convolutional networks for aspect-based sentiment analysis R Li, H Chen, F Feng, Z Ma, X Wang, E Hovy Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 397 | 2021 |
| Enhanced multi-channel graph convolutional network for aspect sentiment triplet extraction H Chen, Z Zhai, F Feng, R Li, X Wang Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 145 | 2022 |
| Deep correspondence restricted Boltzmann machine for cross-modal retrieval F Feng, R Li, X Wang Neurocomputing 154, 50-60, 2015 | 73 | 2015 |
| Multi-scale Two-way Deep Neural Network for Stock Trend Prediction. G Liu, Y Mao, Q Sun, H Huang, W Gao, X Li, J Shen, R Li, X Wang IJCAI, 4555-4561, 2020 | 56 | 2020 |
| Differential networks for visual question answering C Wu, J Liu, X Wang, R Li Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 8997-9004, 2019 | 49 | 2019 |
| Exploring global and local linguistic representations for text-to-image synthesis R Li, N Wang, F Feng, G Zhang, X Wang IEEE Transactions on Multimedia 22 (12), 3075-3087, 2020 | 48 | 2020 |
| Show and Tell More: Topic-Oriented Multi-Sentence Image Captioning. Y Mao, C Zhou, X Wang, R Li IJCAI, 4258-4264, 2018 | 46 | 2018 |
| Dual-CNN: A Convolutional language decoder for paragraph image captioning R Li, H Liang, Y Shi, F Feng, X Wang Neurocomputing 396, 92-101, 2020 | 45 | 2020 |
| Offline Urdu Nastaleeq optical character recognition based on stacked denoising autoencoder I Ahmad, X Wang, R Li, S Rasheed China Communications 14 (1), 146-157, 2017 | 43 | 2017 |
| Correspondence autoencoders for cross-modal retrieval F Feng, X Wang, R Li, I Ahmad ACM Transactions on Multimedia Computing, Communications, and Applications …, 2015 | 41 | 2015 |
| Line and ligature segmentation of Urdu Nastaleeq text I Ahmad, X Wang, R Li, M Ahmed, R Ullah IEEE access 5, 10924-10940, 2017 | 36 | 2017 |
| Fog computing architecture-based data acquisition for WSN applications G Zhang, R Li China Communications 14 (11), 69-81, 2017 | 31 | 2017 |
| Retrieving real world clothing images via multi-weight deep convolutional neural networks R Li, F Feng, I Ahmad, X Wang Cluster Computing 22 (Suppl 3), 7123-7134, 2019 | 30 | 2019 |
| Towards aesthetics of image: a Bayesian framework for color harmony modeling P Lu, X Peng, R Li, X Wang Signal Processing: Image Communication 39, 487-498, 2015 | 30 | 2015 |
| COM-MRC: A COntext-masked machine reading comprehension framework for aspect sentiment triplet extraction Z Zhai, H Chen, F Feng, R Li, X Wang Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | 28 | 2022 |
| Multiple features with extreme learning machines for clothing image recognition R Li, W Lu, H Liang, Y Mao, X Wang Ieee Access 6, 36283-36294, 2018 | 26 | 2018 |
| An EL-LDA based general color harmony model for photo aesthetics assessment P Lu, X Peng, X Zhu, R Li Signal Processing 120, 731-745, 2016 | 25 | 2016 |
| Discovering harmony: A hierarchical colour harmony model for aesthetics assessment P Lu, Z Kuang, X Peng, R Li Computer Vision--ACCV 2014: 12th Asian Conference on Computer Vision …, 2015 | 21 | 2015 |
Fangxiang FengBeijing University of Posts and TelecommunicationsEmail verificata su bupt.edu.cn
