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2020 – today
- 2024
[j9]Yinghao Yao, Jiaying Yang, Haojun Sun, Hengte Kong, Sheng Wang, Ke Xu, Wei Dai, Siyi Jiang, Qingshi Bai, Shilai Xing, Jian Yuan, Xinting Liu, Fan Lu, Zhenhui Chen, Jia Qu, Jianzhong Su
:
DeepGraFT: A novel semantic segmentation auxiliary ROI-based deep learning framework for effective fundus tessellation classification. Comput. Biol. Medicine 169: 107881 (2024)- [j8]Kaiyu Zhang, Fei Wu, Haojun Sun, Meiyu Cai:
Monocular vehicle speed detection based on improved YOLOX and DeepSORT. Neural Comput. Appl. 36(17): 9643-9660 (2024) - [j7]Zhiyu Lyu, Yan Chen, Haojun Sun, Yimin Hou:
A dual fusion deep convolutional network for blind universal image denoising. Signal Process. Image Commun. 120: 117077 (2024) - [c11]Wei Dai, Yinghao Yao, Hengte Kong, Zhen Ji Chen, Sheng Wang, Qingshi Bai, Haojun Sun, Yongxin Yang, Jianzhong Su:
RIP-AV: Joint Representative Instance Pre-training with Context Aware Network for Retinal Artery/Vein Segmentation. MICCAI (1) 2024: 764-774 - [i1]Haojun Sun, Chen Tang, Zhi Wang, Yuan Meng, Jingyan Jiang, Xinzhu Ma, Wenwu Zhu:
TMPQ-DM: Joint Timestep Reduction and Quantization Precision Selection for Efficient Diffusion Models. CoRR abs/2404.09532 (2024) - 2022
- [c10]Guizhong Xu, Haojun Sun:
Modifiable Blockchain Based on Chebyshev Polynomial and Chameleon Hash Function. WISA 2022: 732-739 - [c9]Junjie Liang, Hang Gao, Haojun Sun, Rui Li, Cheng Liu:
Reliable Self-Supervised Information Mining for Deep Subspace Clustering. ICME 2022: 1-6 - 2021
- [j6]Rongbo Chen, Haojun Sun, Lifei Chen, Jianfei Zhang, Shengrui Wang:
Dynamic order Markov model for categorical sequence clustering. J. Big Data 8(1): 154 (2021) - [c8]Jiamin Xu, Haojun Sun:
Sleep Analysis During Light Sleep Based on K-means Clustering and BiLSTM. WISA 2021: 207-214
2010 – 2019
- 2018
- [j5]Jianzhou Zhan, Mei Sun, Huidan Wu, Haojun Sun:
Using triangles and latent factor cosine similarity prior to improve community detection in multi-relational social networks. Concurr. Comput. Pract. Exp. 30(16) (2018) - 2017
- [j4]Haojun Sun, Rongbo Chen, Yong Qin, Shengrui Wang:
Holo-Entropy Based Categorical Data Hierarchical Clustering. Informatica 28(2): 303-328 (2017) - 2015
- [c7]Haojun Sun, Rongbo Chen, Shulin Jin, Yong Qin:
A Hierarchical Clustering for Categorical Data Based on Holo-Entropy. IEEE WISA 2015: 269-274 - 2012
- [c6]Haojun Sun, Tao Wu, Meijuan Yan, Yunxia Wu:
A New Item Clustering-Based Collaborative Filtering Approach. WISA 2012: 91-94 - 2011
- [j3]Haojun Sun, Shengrui Wang:
Measuring the component overlapping in the Gaussian mixture model. Data Min. Knowl. Discov. 23(3): 479-502 (2011) - [c5]Haojun Sun, Qingnan Zeng:
Clustering-Based Touching-Cells Division. WISA 2011: 137-142
2000 – 2009
- 2009
- [c4]Mei Sun, Langhuan Xiong, Haojun Sun, Dazhi Jiang:
A GA-Based Feature Selection for High-Dimensional Data Clustering. WGEC 2009: 769-772 - 2008
- [c3]Haojun Sun, Zhihui Liu, Lingjun Kong:
A Document Clustering Method Based on Hierarchical Algorithm with Model Clustering. AINA Workshops 2008: 1229-1233 - 2006
- [j2]Mohamed Bouguessa, Shengrui Wang, Haojun Sun:
An objective approach to cluster validation. Pattern Recognit. Lett. 27(13): 1419-1430 (2006) - 2005
- [c2]Haojun Sun, Mei Sun:
Trail-and-Error Approach for Determining the Number of Clusters. ICMLC 2005: 229-238 - 2004
- [j1]Haojun Sun, Shengrui Wang, Qingshan Jiang:
FCM-Based Model Selection Algorithms for Determining the Number of Clusters. Pattern Recognit. 37(10): 2027-2037 (2004) - [c1]Haojun Sun, Shengrui Wang:
Distinguishing between overlapping components in mixture models. Neural Networks and Computational Intelligence 2004: 102-108
Coauthor Index
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