Tiejun Yang

VLDB 2026 Research / reviewers in the wild / expert

dblp:24/207 · DBLP profile ↗

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19ranked-venue papers

4as first author

16since 2021 · last 2026

—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 12 · 11 since 2021Graphics, computer vision, multimedia, augmented reality and games · 6 · 4 first-author · 4 since 2021Databases, data management, data science and information retrieval · 1 · 1 since 2021

Year	Publication	Venue	Position
2026	A unified multimodal framework for jointly detecting news veracity and generation provenance Qingfan Zhang, Huifang Hou, Xiaqiong Fan, Tiejun Yang, Chunhua Zhu	Expert Syst. Appl.	6
2026	Multi-graph fusion guided robust adaptive learning for subspace clustering Jianyu Miao, Xiaochan Zhang, Tiejun Yang, Yingjie Tian 0001, Yong Shi 0001	Expert Syst. Appl.	4
2026	Multi-domain fake news detection with synergistic multi-attention Qingfan Zhang, Chensu Zhao, Congrui Zhang, Xiaqiong Fan, Huifang Hou, Tiejun Yang	Knowl. Based Syst.	8
2026	Sparse subspace learning based redundancy-aware unsupervised feature selection Jianyu Miao, Tiejun Yang, Yingjie Tian 0001	Pattern Recognit.	3
2025	Robust sparse orthogonal basis clustering for unsupervised feature selection Jianyu Miao, Tiejun Yang, Yingjie Tian 0001, Yong Shi 0001	Expert Syst. Appl.	3
2025	Broad feature extraction and multi-directional imbalanced weighted broad learning system for the unsupervised stereo matching method Fanman Meng, Tiejun Yang, Huifang Hou, Quan Pan 0001	Expert Syst. Appl.	4
2024	A traffic flow prediction method based on constrained dynamic graph convolutional recurrent networks Hongxiang Xiao, Tiejun Yang	Eng. Appl. Artif. Intell.	3
2024	Explicit unsupervised feature selection based on structured graph and locally linear embedding Jianyu Miao, Tiejun Yang, Yingjie Tian 0001, Yong Shi 0001	Expert Syst. Appl.	3
2023	Multi-directional broad learning system for the unsupervised stereo matching method Niu Ying, Fanman Meng, Tiejun Yang, Xiaozhen Ren, Cao Kun	Pattern Recognit.	4
2022	Self-paced non-convex regularized analysis-synthesis dictionary learning for unsupervised feature selection Jianyu Miao, Tiejun Yang, Zhensong Chen 0001, Xuan Fei, Xuchan Ju, Ke Wang 0064, Mingliang Xu 0001	Knowl. Based Syst.	2
2022	Piezoresistor defect classification using convolutional neural networks based on incremental branch growth Yi-gong Zhao, Tiejun Yang	Multim. Tools Appl.	3
2022	Graph regularized locally linear embedding for unsupervised feature selection Jianyu Miao, Tiejun Yang, Xuan Fei, Lingfeng Niu, Yong Shi 0001	Pattern Recognit.	2
2022	Vehicle counting method based on attention mechanism SSD and state detection Tiejun Yang, Ruiqiang Liang	Vis. Comput.	1
2021	Discriminative group-sparsity constrained broad learning system for visual recognition Junwei Jin 0001, Tiejun Yang, Junwei Duan, C. L. Philip Chen	Inf. Sci.	3
2021	Classification of industrial surface defects based on neural architecture search Tiejun Yang	Multim. Tools Appl.	1
2021	Detection of defects in voltage-dependent resistors using stacked-block-based convolutional neural networks Tiejun Yang	Vis. Comput.	1
2020	Surface defect detection of voltage-dependent resistors using convolutional neural networks Tiejun Yang, Shan Peng	Multim. Tools Appl.	1
2007	A General Method for Detecting All-Zero Blocks Prior to DCT and Quantization abstract This paper presents an innovative algorithm for detecting all-zero discrete cosine transform (DCT) coefficient blocks prior to DCT and quantization for all block-based video coding standards. A mathematic model is established based on analyzing DCT coefficient distribution and applying Paseval energy conservation theorem. The algorithm is applied to H.264 video coding and experimental results show up to 32% higher detection ratio without degrading video quality, compared with results of the existing methods. Furthermore, up to 47% higher detection ratio is achieved by changing the threshold based on DCT coefficient distribution. For motion estimation, much less search points needed by using the proposed method as early termination criterion than that by using the existing methods Zhengguang Xie, James Liu, Tiejun Yang	IEEE Trans. Circuits Syst. Video Technol.	4
2006	A New Approach to Symbolic Classification Rule Extraction Based on SVM Dexian Zhang, Tiejun Yang, Yanfeng Fan	PRICAI	2