Berat Kurar Barakat

24 papers A 1B 6Journal 7Unranked 10

Year	Rank	Type	Title / Venue / Authors
2022	J	`jnl`	Digital Hebrew Paleography: Script Types and Modes. J. Imaging Ahmad Droby, Irina Rabaev, Daria Vasyutinsky Shapira, Berat Kurar Barakat, Jihad El-Sana
2022	B	`conf`	Hard and Soft Labeling for Hebrew Paleography: A Case Study. DAS Ahmad Droby, Daria Vasyutinsky Shapira, Irina Rabaev, Berat Kurar Barakat, Jihad El-Sana
2021	J	`jnl`	Text Line Segmentation for Challenging Handwritten Document Images Using Fully Convolutional Network. CoRR Berat Kurar Barakat, Ahmad Droby, Majeed Kassis, Jihad El-Sana
2021	J	`jnl`	Text line extraction using fully convolutional network and energy minimization. CoRR Berat Kurar Barakat, Ahmad Droby, Reem Alaasam, Boraq Madi, Irina Rabaev, Jihad El-Sana
2021	J	`jnl`	Unsupervised Deep Learning for Handwritten Page Segmentation. CoRR Ahmad Droby, Berat Kurar Barakat, Boraq Madi, Reem Alaasam, Jihad El-Sana
2021	—	`conf`	Unsupervised Learning of Text Line Segmentation by Differentiating Coarse Patterns. ICDAR (2) Berat Kurar Barakat, Ahmad Droby, Raid Saabni, Jihad El-Sana
2021	J	`jnl`	Unsupervised learning of text line segmentation by differentiating coarse patterns. CoRR Berat Kurar Barakat, Ahmad Droby, Raid Saabni, Jihad El-Sana
2021	—	`conf`	VML-HP: Hebrew Paleography Dataset. ICDAR (4) Ahmad Droby, Berat Kurar Barakat, Daria Vasyutinsky Shapira, Irina Rabaev, Jihad El-Sana
2021	J	`jnl`	VML-MOC: Segmenting a multiply oriented and curved handwritten text lines dataset. CoRR Berat Kurar Barakat, Rafi Cohen, Irina Rabaev, Jihad El-Sana
2020	—	`conf`	Deep learning for paleographic analysis of medieval Hebrew manuscripts: a DH team collaboration experience. TwinTalks@DH/DHN Daria Vasyutinsky Shapira, Irina Rabaev, Berat Kurar Barakat, Ahmad Droby, Jihad El-Sana
2020	—	`conf`	Text Line Extraction Using Fully Convolutional Network and Energy Minimization. ICPR Workshops (7) Berat Kurar Barakat, Ahmad Droby, Reem Alaasam, Boraq Madi, Irina Rabaev, Jihad El-Sana
2020	B	`conf`	The HHD Dataset. ICFHR Irina Rabaev, Berat Kurar Barakat, Alexander Churkin, Jihad El-Sana
2020	B	`conf`	Unsupervised Deep Learning for Handwritten Page Segmentation. ICFHR Ahmad Droby, Berat Kurar Barakat, Boraq Madi, Reem Alaasam, Jihad El-Sana
2020	B	`conf`	Unsupervised deep learning for text line segmentation. ICPR Berat Kurar Barakat, Ahmad Droby, Reem Alaasam, Boraq Madi, Irina Rabaev, Raed Shammes, Jihad El-Sana
2020	J	`jnl`	Unsupervised text line segmentation. CoRR Berat Kurar Barakat, Ahmad Droby, Rym Alasam, Boraq Madi, Irina Rabaev, Raed Shammes, Jihad El-Sana
2019	A	`conf`	The Pinkas Dataset. ICDAR Berat Kurar Barakat, Jihad El-Sana, Irina Rabaev
2019	—	`conf`	VML-MOC: Segmenting a Multiply Oriented and Curved Handwritten Text Line Dataset. ASAR@ICDAR Berat Kurar Barakat, Rafi Cohen, Jihad El-Sana
2018	—	`conf`	ASAR 2018 Competition Page Layout Analysis Using Fully Convolutional Networks. ASAR Ahmad Droby, Berat Kurar Barakat, Jihad El-Sana
2018	—	`conf`	Binarization Free Layout Analysis for Arabic Historical Documents Using Fully Convolutional Networks. ASAR Berat Kurar Barakat, Jihad El-Sana
2018	—	`conf`	Case Study: Fine Writing Style Classification Using Siamese Neural Network. ASAR Alaa Abdalhaleem, Berat Kurar Barakat, Jihad El-Sana
2018	—	`conf`	Synthesizing versus Augmentation for Arabic Word Recognition with Convolutional Neural Networks. ASAR Reem Alaasam, Berat Kurar Barakat, Jihad El-Sana
2018	B	`conf`	Text Line Segmentation for Challenging Handwritten Document Images using Fully Convolutional Network. ICFHR Berat Kurar Barakat, Ahmad Droby, Majeed Kassis, Jihad El-Sana
2018	B	`conf`	Word Spotting Using Convolutional Siamese Network. DAS Berat Kurar Barakat, Reem Alaasam, Jihad El-Sana
2017	—	`conf`	Experiment study on utilizing convolutional neural networks to recognize historical Arabic handwritten text. ASAR Reem Alaasam, Berat Kurar Barakat, Majeed Kassis, Jihad El-Sana

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.