代表性论文成果(1作或通讯)
当前位置: 中南大学郭克华的主页 >> 代表性论文成果(1作或通讯)- [21]Sheng Ren, Kehua Guo(通讯), Xiaokang Zhou, Bin Hu, Feihong Zhu, Entao Luo. Medical image super-resolution based on semantic perception transfer learning. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2022, 20: 2598-2609.
- [22]Kehua Guo, Xiangyuan Zhu, Gerald Schaefer, Rui Ding, Hui Fang. Self-supervised memory learning for scene text image super-resolution, Expert Systems with Applications, 2024.
- [23]Kehua Guo, Changchun Shen, Xiaokang Zhou, Sheng Ren, Min Hu, Minxue Shen, Xiang Chen, Haifu Guo. Traffic data-empowered XGBoost-LSTM framework for infectious disease prediction. IEEE Transactions on Intelligent Transportation Systems, 2022, 25(1): 774-785.
- [24]Xiangyuan Zhu, Kehua Guo(通讯), Sheng Ren, Bin Hu, Min Hu, Hui Fang. Lightweight image super-resolution with expectation-maximization attention mechanism. IEEE Transactions on Circuits and Systems for Video Technology, 2021, 32: 1273-1284.
- [25]Bin Hu,Kehua Guo(通讯), Sheng Ren，Hui Fang.Enhancing Robustness of Backdoor Attacks Against Backdoor Defenses.Expert Systems With Applications,2025.
- [26]Jian Zhang, Ze Tao, Kehua Guo(通讯), Haowei Li, Shichao Zhang. Hybrid mix-up contrastive knowledge distillation. Information Sciences, 2024.
- [27]Kehua Guo, Sheng Ren, Zakirul Bhuiyan, Ting Li, Dengchao Liu, Xiang Chen. MDMaaS: medical-assisted diagnosis model as a service with artificial intelligence and trust. IEEE Transactions on Industrial Informatics, 2019, 16(3): 2102-2114.
- [28]Zheng Wu, Feihong Zhu, Kehua Guo(通讯), Ren Sheng, Liu Chao, Hui Fang. Modal Adaptive Super-Resolution for Medical Images via Continual Learning. Signal Processing, Accepted, 2023.
- [29]Zheng Wu, Changchun Shen, Kehua Guo (通讯), Entao Luo, Liwei Wang. NC2E: Boosting Few-shot Learning with Novel Class Center Estimation. Neural Computing and Applications, online. (Q1)
- [30]Zheng Wu, Kehua Guo(通讯), Entao Luo, Tian Wang, Shoujin Wang, Yi Yang, Xiangyuan Zhu, Rui Ding. Medical long-tailed learning for imbalanced data: Bibliometric analysis. Computer Methods and Programs in Biomedicine, 2024, accepted and online.
- [31]Bin Hu, Kehua Guo(通讯), Xiaokang Wang, Jian Zhang, Di Zhou. RRL-GAT: Graph attention network-driven multilabel image robust representation learning. IEEE Internet of Things Journal, 9(12):9167-9178.(IF=10.238, Q1, 高被引)
- [32]Kehua Guo, Bin Hu, Jianhua Ma, Sheng Ren, Ze Tao, Jian Zhang. Toward anomaly behavior detection as an edge network service using a dual-task interactive guided neural network. IEEE Internet of Things Journal, 2020, 16, 12623 - 12637.(IF=10.238, Q1)
- [33]Bin Hu, Kehua Guo(通讯), Jian Zhang, Sheng Ren, Jianhua Ma. Exploring a humanoid video-understanding algorithm guided by behavior. IEEE Computer, 2020,53(8): 59-67.(Q2)
- [34]Kehua Guo, Tao Xu, Xiaoyan Kui, Ruifang Zhang, Tao Chi. iFusion: Towards efficient intelligence fusion for deep learning from real-time and heterogeneous data. Information Fusion, 2019, 51: 215-223.(IF=17.564, Q1)
- [35]Xiangyuan Zhu, Kehua Guo(通讯), Tian Qiu, et al. Stereoscopic Image Super-Resolution with Interactive Memory Learning. Expert Systems With Applications, 2023.(Q1,IF=8.665)
- [36]Kehua Guo, Jie Chen, Tian Qiu, Shaojun Guo, Tao Luo, Tianyu Chen, Sheng Ren. MedGAN: An adaptive GAN approach for medical image generation. Computers in Biology and Medicine, 2023.
- [37]Sheng Ren, Yan He, Xiaokang Wang, Kehua Guo(通讯), Silvio Barra, Jianqi Li .？CIOD: an intelligent class-incremental object detection system with nearest mean of exemplars.？J Ambient Intell Human Comput (2022, Q1). https://doi.org/10.1007/s12652-022-04341-7
- [38]Kehua Guo, Zhonghe Liang, Ronghua Shi, Chao Hu, Zuoyong Li. Transparent learning: an incremental machine learning framework based on transparent computing. IEEE Network, 2018, 32: 146-151.(IF=10.294, Q1)
- [39]Kehua Guo, Yayuan Tang, Ping Zhang. CSF: Crowdsourcing semantic fusion for heterogeneous media big data in the internet of things. Information Fusion, 2017, 37: 77-85.(IF=17.564, Q1)
- [40]Jiancun Zhou, Zheng Wu, Zixi Jiang, Kai Huang, Kehua Guo(通讯), Shuang Zhao. Background selection schema on deep learning-based classification of dermatological disease. Computers In Biology and Medicine 149: 105966 (2022).