Zhengeng Yang - RankMe

28 papers A* 3Journal 24Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Efficient Point Cloud Processing with High-Dimensional Positional Encoding and Non-Local MLPs. CoRR Yanmei Zou, Hongshan Yu, Yaonan Wang, Zhengeng Yang, Xieyuanli Chen, Kailun Yang, Naveed Akhtar
2025	J	`jnl`	Deep learning based 3D segmentation in computer vision: A survey. Inf. Fusion Yong He, Hongshan Yu, Xiaoyan Liu, Zhengeng Yang, Wei Sun, Saeed Anwar, Ajmal Mian
2025	J	`jnl`	Deep learning based infrared small object segmentation: Challenges and future directions. CoRR Zhengeng Yang, Hongshan Yu, Jianjun Zhang, Qiang Tang, Ajmal Mian
2025	J	`jnl`	Deep learning based infrared small object segmentation: Challenges and future directions. Inf. Fusion Zhengeng Yang, Hongshan Yu, Jianjun Zhang, Qiang Tang, Ajmal Mian
2025	J	`jnl`	Full Point Encoding for Local Feature Aggregation in 3-D Point Clouds. IEEE Trans. Neural Networks Learn. Syst. Yong He, Hongshan Yu, Zhengeng Yang, Xiaoyan Liu, Wei Sun, Ajmal Mian
2024	J	`jnl`	3D point cloud-based place recognition: a survey. Artif. Intell. Rev. Kan Luo, Hongshan Yu, Xieyuanli Chen, Zhengeng Yang, Jingwen Wang, Panfei Cheng, Ajmal Mian
2024	J	`jnl`	Domain-Invariant Prototypes for Semantic Segmentation. IEEE Trans. Circuits Syst. Video Technol. Zhengeng Yang, Hongshan Yu, Wei Sun, Li Cheng, Ajmal Mian
2024	J	`jnl`	Fine-Grained Semantic Information Preservation and Misclassification-Aware Loss for 3D Point Cloud. IEEE Robotics Autom. Lett. Yanmei Zou, Xuefei Lin, Hongshan Yu, Zhengeng Yang, Naveed Akhtar
2024	J	`jnl`	Fully Convolutional Network-Based Self-Supervised Learning for Semantic Segmentation. IEEE Trans. Neural Networks Learn. Syst. Zhengeng Yang, Hongshan Yu, Yong He, Wei Sun, Zhi-Hong Mao, Ajmal Mian
2024	A*	`conf`	Improved MLP Point Cloud Processing with High-Dimensional Positional Encoding. AAAI Yanmei Zou, Hongshan Yu, Zhengeng Yang, Zechuan Li, Naveed Akhtar
2024	A*	`conf`	OST: Refining Text Knowledge with Optimal Spatio-Temporal Descriptor for General Video Recognition. CVPR Tom Tongjia Chen, Hongshan Yu, Zhengeng Yang, Zechuan Li, Wei Sun, Chen Chen
2023	A*	`conf`	AShapeFormer : Semantics-Guided Object-Level Active Shape Encoding for 3D Object Detection via Transformers. CVPR Zechuan Li, Hongshan Yu, Zhengeng Yang, Tom Tongjia Chen, Naveed Akhtar
2023	J	`jnl`	DANet: Density Adaptive Convolutional Network With Interactive Attention for 3D Point Clouds. IEEE Robotics Autom. Lett. Yong He, Hongshan Yu, Zhengeng Yang, Wei Sun, Mingtao Feng, Ajmal Mian
2023	J	`jnl`	DANet: Density Adaptive Convolutional Network with Interactive Attention for 3D Point Clouds. CoRR Yong He, Hongshan Yu, Zhengeng Yang, Wei Sun, Mingtao Feng, Ajmal Mian
2023	J	`jnl`	First Place Solution to the CVPR'2023 AQTC Challenge: A Function-Interaction Centric Approach with Spatiotemporal Visual-Language Alignment. CoRR Tom Tongjia Chen, Hongshan Yu, Zhengeng Yang, Ming Li, Zechuan Li, Jingwen Wang, Wei Miao, Wei Sun, Chen Chen
2023	J	`jnl`	Full Point Encoding for Local Feature Aggregation in 3D Point Clouds. CoRR Yong He, Hongshan Yu, Zhengeng Yang, Xiaoyan Liu, Wei Sun, Ajmal Mian
2023	J	`jnl`	OST: Refining Text Knowledge with Optimal Spatio-Temporal Descriptor for General Video Recognition. CoRR Tom Tongjia Chen, Hongshan Yu, Zhengeng Yang, Zechuan Li, Wei Sun, Chen Chen
2022	J	`jnl`	Domain-invariant Prototypes for Semantic Segmentation. CoRR Zhengeng Yang, Hongshan Yu, Wei Sun, Li Cheng, Ajmal Mian
2022	J	`jnl`	Fast ORB-SLAM Without Keypoint Descriptors. IEEE Trans. Image Process. Qiang Fu, Hongshan Yu, Xiaolong Wang, Zhengeng Yang, Yong He, Hong Zhang, Ajmal Mian
2022	—	`conf`	LA-HRNet: High-Resolution Network for Automatic Left Atrial Segmentation in Multi-center LEG MRI. LAScarQS@MICCAI Tongtong Xie, Zhengeng Yang, Hongshan Yu
2021	J	`jnl`	Deep Learning based 3D Segmentation: A Survey. CoRR Yong He, Hongshan Yu, Xiaoyan Liu, Zhengeng Yang, Wei Sun, Yaonan Wang, Qiang Fu, Yanmei Zou, Ajmal Mian
2021	J	`jnl`	NDNet: Narrow While Deep Network for Real-Time Semantic Segmentation. IEEE Trans. Intell. Transp. Syst. Zhengeng Yang, Hongshan Yu, Qiang Fu, Wei Sun, Wenyan Jia, Mingui Sun, Zhi-Hong Mao
2020	J	`jnl`	FastORB-SLAM: a Fast ORB-SLAM Method with Coarse-to-Fine Descriptor Independent Keypoint Matching. CoRR Qiang Fu, Hongshan Yu, Xiaolong Wang, Zhengeng Yang, Hong Zhang, Ajmal Mian
2020	J	`jnl`	Self-supervised Learning with Fully Convolutional Networks. CoRR Zhengeng Yang, Hongshan Yu, Yong He, Zhi-Hong Mao, Ajmal Mian
2020	J	`jnl`	Small Object Augmentation of Urban Scenes for Real-Time Semantic Segmentation. IEEE Trans. Image Process. Zhengeng Yang, Hongshan Yu, Mingtao Feng, Wei Sun, Xuefei Lin, Mingui Sun, Zhi-Hong Mao, Ajmal Mian
2019	J	`jnl`	Locally Shared Features: An Efficient Alternative to Conditional Random Field for Semantic Segmentation. IEEE Access Zhengeng Yang, Hongshan Yu, Wei Sun, Zhihong Mao, Mingui Sun
2019	J	`jnl`	Real time backbone for semantic segmentation. CoRR Zhengeng Yang, Hongshan Yu, Qiang Fu, Wei Sun, Wenyan Jia, Mingui Sun, Zhi-Hong Mao
2018	J	`jnl`	Methods and datasets on semantic segmentation: A review. Neurocomputing Hongshan Yu, Zhengeng Yang, Lei Tan, Yaonan Wang, Wei Sun, Mingui Sun, Yandong Tang

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.