Abder-Rahman Ali

18 papers B 1C 1Journal 7Unranked 8

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Prompt-driven Universal Model for View-Agnostic Echocardiography Analysis. CoRR Sekeun Kim, Hui Ren, Peng Guo, Abder-Rahman Ali, Patrick Zhang, Kyungsang Kim, Xiang Li, Quanzheng Li
2024	—	`conf`	Simple is More: Efficient Liver View Classification in Ultrasound Images Using Minimal Labeled Data and Simple Neural Network Architecture. DEMI@MICCAI Abder-Rahman Ali, Anthony E. Samir
2023	—	`conf`	Liver Segmentation in Ultrasound Images Using Self-Supervised Learning with Physics-inspired Augmentation and Global-Local Refinement. Canadian AI Abder-Rahman Ali, Peng Guo, Anthony E. Samir
2023	—	`conf`	Self-Supervised Learning for Accurate Liver View Classification in Ultrasound Images with Minimal Labeled Data. CVPR Workshops Abder-Rahman Ali, Anthony E. Samir, Peng Guo
2022	J	`jnl`	A fuzzy-enhanced deep learning approach for early detection of Covid-19 pneumonia from portable chest X-ray images. Neurocomputing Cosimo Ieracitano, Nadia Mammone, Mario Versaci, Giuseppe Varone, Abder-Rahman Ali, Antonio Armentano, Grazia Calabrese, Anna Ferrarelli, Lorena Turano, Carmela Tebala, Zain U. Hussain, Zakariya Sheikh, Aziz Sheikh, Giuseppe Sceni, Amir Hussain, Francesco Carlo Morabito
2020	J	`jnl`	A machine learning approach to automatic detection of irregularity in skin lesion border using dermoscopic images. PeerJ Comput. Sci. Abder-Rahman Ali, Jingpeng Li, Guang Yang, Sally Jane O'Shea
2020	J	`jnl`	Automating the ABCD Rule for Melanoma Detection: A Survey. IEEE Access Abder-Rahman Ali, Jingpeng Li, Guang Yang
2019	B	`conf`	A Deep Learning Based Approach to Skin Lesion Border Extraction With a Novel Edge Detector in Dermoscopy Images. IJCNN Abder-Rahman Ali, Jingpeng Li, Sally Jane O'Shea, Guang Yang, Thomas Trappenberg, Xujiong Ye
2019	J	`jnl`	Skin cancer detection based on deep learning and entropy to detect outlier samples. CoRR André G. C. Pacheco, Abder-Rahman Ali, Thomas Trappenberg
2019	—	`conf`	Supervised Versus Unsupervised Deep Learning Based Methods for Skin Lesion Segmentation in Dermoscopy Images. Canadian AI Abder-Rahman Ali, Jingpeng Li, Thomas Trappenberg
2016	J	`jnl`	Fuzzy C-Means based on Minkowski distance for liver CT image segmentation. Intell. Decis. Technol. Abder-Rahman Ali, Micael S. Couceiro, Aboul Ella Hassanien, D. Jude Hemanth
2016	—	`ch.`	Particle Swarm Optimization Based Fast Fuzzy C-Means Clustering for Liver CT Segmentation. Applications of Intelligent Optimization in Biology and Medicine Abder-Rahman Ali, Micael S. Couceiro, Ahmed M. Anter, Aboul Ella Hassanien
2015	J	`jnl`	A Novel Evolutionary Swarm Fuzzy Clustering Approach for Hyperspectral Imagery. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. Pedram Ghamisi, Abder-Rahman Ali, Micael S. Couceiro, Jón Atli Benediktsson
2015	—	`conf`	Smoothed shock filtered defuzzification with Zernike moments for liver tumor extraction in MR images. IPTA Antoine Vacavant, Abder-Rahman Ali, Manuel Grand-Brochier, Adelaide Albouy-Kissi, Agaicha Alfidja, Pascal Chabrot, Jean-Yves Boire
2014	—	`conf`	Fuzzy C-Means Based Liver CT Image Segmentation with Optimum Number of Clusters. IBICA Abder-Rahman Ali, Micael S. Couceiro, Aboul Ella Hassanien, Mohamed F. Tolba, Václav Snásel
2014	—	`conf`	Liver CT Image Segmentation with an Optimum Threshold Using Measure of Fuzziness. IBICA Abder-Rahman Ali, Micael S. Couceiro, Ahmed M. Anter, Aboul Ella Hassanien, Mohamed F. Tolba, Václav Snásel
2014	C	`conf`	Melanoma detection using fuzzy C-means clustering coupled with mathematical morphology. HIS Abder-Rahman Ali, Micael S. Couceiro, Aboul Ella Hassenian
2014	—	`conf`	PSilhOuette: Towards an Optimal Number of Clusters Using a Nested Particle Swarm Approach for Liver CT Image Segmentation. AMLTA Abder-Rahman Ali, Micael S. Couceiro, Aboul Ella Hassenian

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.