Yan-Ming Zhang

40 papers A* 4A 1B 3Misc 1Journal 18Unranked 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Air Quality Prediction With a Meteorology-Guided Modality-Decoupled Spatiotemporal Network. IEEE Trans. Artif. Intell. Hang Yin, Yan-Ming Zhang, Jian Xu, Jianlong Chang, Yin Li, Cheng-Lin Liu
2025	—	`conf`	FLUX-Font: Stylized Font Generation Based on Fine-Tuning Pre-trained Diffusion Transformer. ACPR (1) Zheyu Li, Honglie Wang, Yan-Ming Zhang, Cheng-Lin Liu
2024	—	`conf`	Class Incremental Learning for Character String Recognition. ICDAR (5) Yijie Hu, Yan-Ming Zhang, Kaizhu Huang, Qiu-Feng Wang
2024	—	`conf`	Document Specular Highlight Removal with Coarse-to-Fine Strategy. ICDAR (1) Xin Yang, Fei Yin, Yan-Ming Zhang, Xudong Yan, Tao Xue
2024	J	`jnl`	Transformer-based stroke relation encoding for online handwriting and sketches. Pattern Recognit. Jing-Yu Liu, Yan-Ming Zhang, Fei Yin, Cheng-Lin Liu
2023	—	`conf`	Diff-Writer: A Diffusion Model-Based Stylized Online Handwritten Chinese Character Generator. ICONIP (10) Minsi Ren, Yan-Ming Zhang, Qiu-Feng Wang, Fei Yin, Cheng-Lin Liu
2023	J	`jnl`	DyGAT: Dynamic stroke classification of online handwritten documents and sketches. Pattern Recognit. Yu-Ting Yang, Yan-Ming Zhang, Xiao-Long Yun, Fei Yin, Cheng-Lin Liu
2023	Misc	`conf`	Streaming Stroke Classification of Online Handwriting. ICASSP Jing-Yu Liu, Yan-Ming Zhang, Fei Yin, Cheng-Lin Liu
2022	J	`jnl`	Adaptable Global Network for Whole-Brain Segmentation with Symmetry Consistency Loss. Cogn. Comput. Yuan-Xing Zhao, Yan-Ming Zhang, Ming Song, Cheng-Lin Liu
2022	J	`jnl`	Instance GNN: A Learning Framework for Joint Symbol Segmentation and Recognition in Online Handwritten Diagrams. IEEE Trans. Multim. Xiao-Long Yun, Yan-Ming Zhang, Fei Yin, Cheng-Lin Liu
2021	—	`conf`	An Abused Webpage Detection Method Based on Screenshots Text Recognition. ICEA Yan-Ming Huang, Dongjie Liu, Zhiwei Yan, Yan-Ming Zhang, Guang-Gang Geng
2021	—	`conf`	CASIA-onDo: A New Database for Online Handwritten Document Analysis. ACPR (2) Yu-Ting Yang, Yan-Ming Zhang, Xiao-Long Yun, Fei Yin, Cheng-Lin Liu
2021	A*	`conf`	Graph-to-Graph: Towards Accurate and Interpretable Online Handwritten Mathematical Expression Recognition. AAAI Jin-Wen Wu, Fei Yin, Yan-Ming Zhang, Xu-Yao Zhang, Cheng-Lin Liu
2021	J	`jnl`	Joint stroke classification and text line grouping in online handwritten documents with edge pooling attention networks. Pattern Recognit. Jun-Yu Ye, Yan-Ming Zhang, Qing Yang, Cheng-Lin Liu
2021	—	`conf`	Region Ensemble Network for MCI Conversion Prediction with a Relation Regularized Loss. MICCAI (5) Yuan-Xing Zhao, Yan-Ming Zhang, Ming Song, Cheng-Lin Liu
2020	J	`jnl`	Contextual Stroke Classification in Online Handwritten Documents with Edge Graph Attention Networks. SN Comput. Sci. Jun-Yu Ye, Yan-Ming Zhang, Qing Yang, Cheng-Lin Liu
2020	J	`jnl`	Handwritten Mathematical Expression Recognition via Paired Adversarial Learning. Int. J. Comput. Vis. Jin-Wen Wu, Fei Yin, Yan-Ming Zhang, Xu-Yao Zhang, Cheng-Lin Liu
2020	J	`jnl`	Online semi-supervised learning with learning vector quantization. Neurocomputing Yuan-Yuan Shen, Yan-Ming Zhang, Xu-Yao Zhang, Cheng-Lin Liu
2019	—	`conf`	Bag of Tricks for 3D MRI Brain Tumor Segmentation. BrainLes@MICCAI (1) Yuan-Xing Zhao, Yan-Ming Zhang, Cheng-Lin Liu
2019	A	`conf`	Contextual Stroke Classification in Online Handwritten Documents with Graph Attention Networks. ICDAR Jun-Yu Ye, Yan-Ming Zhang, Qing Yang, Cheng-Lin Liu
2019	—	`conf`	Multi-view Semi-supervised 3D Whole Brain Segmentation with a Self-ensemble Network. MICCAI (3) Yuan-Xing Zhao, Yan-Ming Zhang, Ming Song, Cheng-Lin Liu
2019	—	`conf`	Online Handwritten Diagram Recognition with Graph Attention Networks. ICIG (1) Xiao-Long Yun, Yan-Ming Zhang, Jun-Yu Ye, Cheng-Lin Liu
2018	B	`conf`	Anomaly Detection via Minimum Likelihood Generative Adversarial Networks. ICPR Chu Wang, Yan-Ming Zhang, Cheng-Lin Liu
2018	J	`jnl`	Drawing and Recognizing Chinese Characters with Recurrent Neural Network. IEEE Trans. Pattern Anal. Mach. Intell. Xu-Yao Zhang, Fei Yin, Yan-Ming Zhang, Cheng-Lin Liu, Yoshua Bengio
2018	—	`conf`	Image-to-Markup Generation via Paired Adversarial Learning. ECML/PKDD (1) Jin-Wen Wu, Fei Yin, Yan-Ming Zhang, Xu-Yao Zhang, Cheng-Lin Liu
2016	J	`jnl`	Adaptive spatial pooling for image classification. Pattern Recognit. Yinglu Liu, Yan-Ming Zhang, Xu-Yao Zhang, Cheng-Lin Liu
2016	J	`jnl`	Drawing and Recognizing Chinese Characters with Recurrent Neural Network. CoRR Xu-Yao Zhang, Fei Yin, Yan-Ming Zhang, Cheng-Lin Liu, Yoshua Bengio
2016	B	`conf`	Joint training of conditional random fields and neural networks for stroke classification in online handwritten documents. ICPR Jun-Yu Ye, Yan-Ming Zhang, Cheng-Lin Liu
2016	A*	`conf`	Large-Scale Graph-Based Semi-Supervised Learning via Tree Laplacian Solver. AAAI Yan-Ming Zhang, Xu-Yao Zhang, Xiao-Tong Yuan, Cheng-Lin Liu
2015	J	`jnl`	Combating phishing attacks via brand identity and authorization features. Secur. Commun. Networks Guang-Gang Geng, Xiao-Dong Lee, Yan-Ming Zhang
2015	J	`jnl`	MTC: A Fast and Robust Graph-Based Transductive Learning Method. IEEE Trans. Neural Networks Learn. Syst. Yan-Ming Zhang, Kaizhu Huang, Guang-Gang Geng, Cheng-Lin Liu
2014	J	`jnl`	Combination of Classification and Clustering Results with Label Propagation. IEEE Signal Process. Lett. Xu-Yao Zhang, Peipei Yang, Yan-Ming Zhang, Kaizhu Huang, Cheng-Lin Liu
2014	B	`conf`	Integrating supervised subspace criteria with restricted Boltzmann Machine for feature extraction. IJCNN Guo-Sen Xie, Xu-Yao Zhang, Yan-Ming Zhang, Cheng-Lin Liu
2014	J	`jnl`	Learning Locality Preserving Graph from Data. IEEE Trans. Cybern. Yan-Ming Zhang, Kaizhu Huang, Xinwen Hou, Cheng-Lin Liu
2014	J	`jnl`	Minimum-risk training for semi-Markov conditional random fields with application to handwritten Chinese/Japanese text recognition. Pattern Recognit. Xiang-Dong Zhou, Yan-Ming Zhang, Feng Tian, Hongan Wang, Cheng-Lin Liu
2013	J	`jnl`	A Taxonomy of Hyperlink Hiding Techniques CoRR Guanggang Geng, Yan-Ming Zhang, Xiao-Dong Lee, Wei Wang, An-Lei Hu
2013	—	`conf`	Fast kNN Graph Construction with Locality Sensitive Hashing. ECML/PKDD (2) Yan-Ming Zhang, Kaizhu Huang, Guanggang Geng, Cheng-Lin Liu
2011	A*	`conf`	Fast and Robust Graph-based Transductive Learning via Minimum Tree Cut. ICDM Yan-Ming Zhang, Kaizhu Huang, Cheng-Lin Liu
2010	A*	`conf`	Transductive Learning on Adaptive Graphs. AAAI Yan-Ming Zhang, Yu Zhang, Dit-Yan Yeung, Cheng-Lin Liu, Xinwen Hou
2009	—	`conf`	Subspace Regularization: A New Semi-supervised Learning Method. ECML/PKDD (2) Yan-Ming Zhang, Xinwen Hou, Shiming Xiang, Cheng-Lin Liu

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.