Tannistha Pal

12 papers B 1Journal 3Unranked 8

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	A transmission model based deep neural network for image dehazing. Multim. Tools Appl. Tannistha Pal, Mritunjoy Halder, Sattwik Barua
2024	—	`conf`	Investigating the Efficacy of Diverse Machine Learning Classifiers for Parkinson's Disease Detection. ICCCNT Sourabarna Roy, Tina Debbarma, Tannistha Pal, Prakash Duraisamy
2023	—	`conf`	A Comparative Analysis of Advanced Machine Learning Algorithms to diagnose Parkinson's Disease. ICMLDE Sourabarna Roy, Tannistha Pal, Swapan Debbarma
2023	—	`conf`	A comparative analysis of chaos theory based medical image steganography to enhance data security. ICMLDE Sharmila Ghosh, Ashim Saha, Tannistha Pal, Anand Kumar Jha
2023	—	`conf`	Prediction of Dangerous Driving Behaviour Based on Vehicle Motion. ICMLDE Tina Debbarma, Tannistha Pal, Nikhil Debbarma
2022	J	`jnl`	Visibility enhancement of fog degraded images using adaptive defogging function. Multim. Tools Appl. Tannistha Pal, Debotosh Bhattacharjee
2021	J	`jnl`	A Robust Method for Dehazing of Single Image with Sky Region Detection and Segmentation. Int. J. Image Graph. Tannistha Pal
2021	B	`conf`	Benchmarking of Natural Scene Image Dataset In Degraded Conditions For Visibility Enhancement. ICIP Sourav Dey Roy, Tannistha Pal, Mrinal Kanti Bhowmik
2018	—	`conf`	A Review on Image Defogging Techniques Based on Dark Channel Prior. CICBA (1) Tannistha Pal, Arghadeep Datta, Taniya Das, Ipsita Das, Dipa Chakma
2018	—	`conf`	Quality Enhancement of Foggy Images Comprising of Large Sky Region on SAMEER TU Dataset. ICCCNT Tannistha Pal, Mrinal Kanti Bhowmik
2018	—	`conf`	Visibility Enhancement of Fog Degraded Image Sequences on SAMEER TU Dataset Using Dark Channel Strategy. ICCCNT Tannistha Pal
2014	—	`conf`	Contrast Restoration of Fog-Degraded Image Sequences. SocProS (1) Tannistha Pal, Mrinal Kanti Bhowmik, Anjan Kumar Ghosh

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.

In 2025, he co-authored Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja, published at CheckMATE. The paper evaluates the effectiveness of obfuscation techniques and their impact on source-level static analysis and binary-level decompilation.

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.