Gang Yang - RankMe

23 papers A* 1B 1Journal 17Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	ESMT: Context-adaptive vision-language tracking with episodic-semantic memory. Appl. Intell. Jiapeng Zhang, Ying Wei, Yongfeng Li, Gang Yang
2026	J	`jnl`	Explicit-Implicit Prompt Injection and Semantic-Guided Latent LoRA for Vision-Language Tracking. IEEE Signal Process. Lett. Jiapeng Zhang, Ying Wei, Yongfeng Li, Gang Yang, Qiaohong Hao
2025	J	`jnl`	A weakly supervised salient object detection framework based on structured scribble. Neurocomputing Congjin Gong, Haoyu Dong, Gang Yang, Pengyu Yang
2025	J	`jnl`	Explicit Semantic Alignment Network for RGB-T salient object detection with Hierarchical Cross-Modal Fusion. Image Vis. Comput. Hongkuan Wang, Qingxi Yu, Zhenguang Di, Gang Yang
2024	J	`jnl`	CSNet: a ConvNeXt-based Siamese network for RGB-D salient object detection. Vis. Comput. Yunhua Zhang, Hangxu Wang, Gang Yang, Jianhao Zhang, Congjin Gong, Yutao Wang
2024	J	`jnl`	Feature differences reduction and specific features preserving network for RGB-T salient object detection. Image Vis. Comput. Qiqi Xu, Zhenguang Di, Haoyu Dong, Gang Yang
2023	J	`jnl`	Eliminating the Influence of Moisture on Solid Concentration Measurement in Gas-Solid Flows Using Combined Sensors. IEEE Trans. Instrum. Meas. Dayang Wang, Jiuxiang Sun, Yutao Wang, Gang Yang, Zengyan Zhu, Zhi Xie
2023	J	`jnl`	TANet: Transformer-based asymmetric network for RGB-D salient object detection. IET Comput. Vis. Chang Liu, Gang Yang, Shuo Wang, Hangxu Wang, Yunhua Zhang, Yutao Wang
2022	J	`jnl`	A Novel and Systematic Signal Extraction Method for High-Temperature Object Detection via Structured Light Vision. IEEE Trans. Instrum. Meas. Qing He, Xingze Zhang, Zhiwen Ji, Han Gao, Gang Yang
2022	J	`jnl`	TANet: Transformer-based Asymmetric Network for RGB-D Salient Object Detection. CoRR Chang Liu, Gang Yang, Shuo Wang, Hangxu Wang, Yunhua Zhang, Yutao Wang
2021	—	`conf`	A Simple Network with Progressive Structure for Salient Object Detection. PRCV (2) Boyi Zhou, Gang Yang, Xin Wan, Yutao Wang, Chang Liu, Hangxu Wang
2021	J	`jnl`	Deep mutual learning for visual object tracking. Pattern Recognit. Haojie Zhao, Gang Yang, Dong Wang, Huchuan Lu
2021	—	`conf`	Feature Enhancement and Multi-scale Cross-Modal Attention for RGB-D Salient Object Detection. PRCV (2) Xin Wan, Gang Yang, Boyi Zhou, Chang Liu, Hangxu Wang, Yutao Wang
2019	—	`conf`	Deep mutual learning for visual tracking. ACM TUR-C Kai Gao, Pingping Zhang, Yan Liu, Ziqin Zhou, Gang Yang, Huchuan Lu
2019	B	`conf`	Lightweight Deep Neural Network for Real-Time Visual Tracking with Mutual Learning. ICIP Haojie Zhao, Gang Yang, Dong Wang, Huchuan Lu
2019	J	`jnl`	Multi attention module for visual tracking. Pattern Recognit. Boyu Chen, Peixia Li, Chong Sun, Dong Wang, Gang Yang, Huchuan Lu
2018	J	`jnl`	An Unsupervised Game-Theoretic Approach to Saliency Detection. IEEE Trans. Image Process. Yu Zeng, Mengyang Feng, Huchuan Lu, Gang Yang, Ali Borji
2018	J	`jnl`	Boundary-Guided Feature Aggregation Network for Salient Object Detection. IEEE Signal Process. Lett. Yun-Zhi Zhuge, Gang Yang, Pingping Zhang, Huchuan Lu
2018	A*	`conf`	Detect Globally, Refine Locally: A Novel Approach to Saliency Detection. CVPR Tiantian Wang, Lihe Zhang, Shuo Wang, Huchuan Lu, Gang Yang, Xiang Ruan, Ali Borji
2013	J	`jnl`	An Effective Framework for Automatic Segmentation of Hard Exudates in Fundus Images. J. Circuits Syst. Comput. Nan Yang, Huchuan Lu, Guo-Liang Fang, Gang Yang
2012	J	`jnl`	Robust Eye Tracking in Video Sequence. J. Circuits Syst. Comput. Huchuan Lu, Shipeng Lu, Gang Yang
2012	J	`jnl`	Tri-Tracking: Combining Three Independent Views for Robust Visual Tracking. Int. J. Image Graph. Dong Wang, Gang Yang, Huchuan Lu
2011	—	`conf`	Robust object tracking by adaptive models combination. iCAST Gang Yang, Dong Wang, Yutao Wang, Zunyi Wang

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.