Dalal AL-Alimi

14 papers Journal 14

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Hybrid Transfer Learning Framework for Enhanced Oil Production Time Series Forecasting. Comput. Mater. Continua Dalal AL-Alimi, Mohammed A. A. Al-qaness, Robertas Damasevicius
2025	J	`jnl`	Hyperspectral image classification using Uniform Manifold Approximation and Projection with fusion deep learning network. Appl. Soft Comput. Chen Lou, Mohammed A. A. Al-qaness, Sike Ni, Dalal AL-Alimi, Robertas Damasevicius, Saeed Hamood Alsamhi
2025	J	`jnl`	Land use/land cover (LULC) classification using hyperspectral images: a review. Geo spatial Inf. Sci. Chen Lou, Mohammed A. A. Al-qaness, Dalal AL-Alimi, Abdelghani Dahou, Mohamed E. Abd Elaziz, Laith Abualigah, Ahmed A. Ewees
2025	J	`jnl`	Multiple lung diseases detection using advanced deep learning model with attention mechanisms and upsampling features. Eng. Appl. Artif. Intell. Jie Zhu, Mohammed A. A. Al-qaness, Dalal AL-Alimi, Heng Zhi Tao, Saeed Hamood Alsamhi
2024	J	`jnl`	A survey on hand gesture recognition based on surface electromyography: Fundamentals, methods, applications, challenges and future trends. Appl. Soft Comput. Sike Ni, Mohammed A. A. Al-qaness, Ammar Hawbani, Dalal AL-Alimi, Mohamed E. Abd Elaziz, Ahmed A. Ewees
2024	J	`jnl`	Fall Detection Systems for Internet of Medical Things Based on Wearable Sensors: A Review. IEEE Internet Things J. Zhiyuan Jiang, Mohammed A. A. Al-qaness, Dalal AL-Alimi, Ahmed A. Ewees, Mohamed Abd Elaziz, Abdelghani Dahou, Ahmed M. Helmi
2024	J	`jnl`	Hyperspectral image classification using graph convolutional network: A comprehensive review. Expert Syst. Appl. Guoyong Wu, Mohammed A. A. Al-qaness, Dalal AL-Alimi, Abdelghani Dahou, Mohamed E. Abd Elaziz, Ahmed A. Ewees
2024	J	`jnl`	MGCET: MLP-mixer and Graph Convolutional Enhanced Transformer for Hyperspectral Image Classification. Remote. Sens. Mohammed A. A. Al-qaness, Guoyong Wu, Dalal AL-Alimi
2023	J	`jnl`	ETR: Enhancing transformation reduction for reducing dimensionality and classification complexity in hyperspectral images. Expert Syst. Appl. Dalal AL-Alimi, Zhihua Cai, Mohammed Abdulaziz Aide Al-qaness, Eman Ahmed Alawamy, Ahamed Alalimi
2023	J	`jnl`	FHIC: Fast Hyperspectral Image Classification Model Using ETR Dimensionality Reduction and ELU Activation Function. IEEE Trans. Geosci. Remote. Sens. Dalal AL-Alimi, Zhihua Cai, Mohammed Abdulaziz Aide Al-qaness
2023	J	`jnl`	IDA: Improving distribution analysis for reducing data complexity and dimensionality in hyperspectral images. Pattern Recognit. Dalal AL-Alimi, Mohammed Abdulaziz Aide Al-qaness, Zhihua Cai, Eman Ahmed Alawamy
2022	J	`jnl`	Compression and reinforce variation with convolutional neural networks for hyperspectral image classification. Appl. Soft Comput. Dalal AL-Alimi, Zhihua Cai, Mohammed Abdulaziz Aide Al-qaness, Abdelghani Dahou, Eman Ahmed Alawamy, Sakinatu Issaka
2022	J	`jnl`	Meta-Learner Hybrid Models to Classify Hyperspectral Images. Remote. Sens. Dalal AL-Alimi, Mohammed Abdulaziz Aide Al-qaness, Zhihua Cai, Abdelghani Dahou, Yuxiang Shao, Sakinatu Issaka
2019	J	`jnl`	Multi-Scale Geospatial Object Detection Based on Shallow-Deep Feature Extraction. Remote. Sens. Dalal AL-Alimi, Yuxiang Shao, Ruyi Feng, Mohammed Abdulaziz Aide Al-qaness, Mohamed E. Abd Elaziz, Sunghwan Kim

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.