Tammy Riklin-Raviv

25 papers A* 2B 1Journal 15Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Boundary-Aware Instance Segmentation in Microscopy Imaging. CoRR Thomas Mendelson, Joshua Francois, Galit Lahav, Tammy Riklin-Raviv
2025	—	`conf`	HyDA: Hypernetworks for Test Time Domain Adaptation in Medical Imaging Analysis. MICCAI (5) Doron Serebro, Tammy Riklin-Raviv
2025	J	`jnl`	HyDA: Hypernetworks for Test Time Domain Adaptation in Medical Imaging Analysis. CoRR Doron Serebro, Tammy Riklin-Raviv
2025	J	`jnl`	Show and Tell: Visually Explainable Deep Neural Nets via Spatially-Aware Concept Bottleneck Models. CoRR Itay Benou, Tammy Riklin-Raviv
2022	J	`jnl`	A Deep Ensemble Learning Approach to Lung CT Segmentation for COVID-19 Severity Assessment. CoRR Tal Ben-Haim, Ron Moshe Sofer, Gal Ben-Arie, Ilan Shelef, Tammy Riklin-Raviv
2022	J	`jnl`	Graph Neural Network for Cell Tracking in Microscopy Videos. CoRR Tal Ben-Haim, Tammy Riklin-Raviv
2020	J	`jnl`	The Role of Regularization in Shaping Weight and Node Pruning Dependency and Dynamics. CoRR Yael Ben-Guigui, Jacob Goldberger, Tammy Riklin-Raviv
2019	J	`jnl`	The Impact of an Inter-rater Bias on Neural Network Training. CoRR Or Shwartzman, Harel Gazit, Ilan Shelef, Tammy Riklin-Raviv
2018	J	`jnl`	DeepTract: A Probabilistic Deep Learning Framework for White Matter Fiber Tractography. CoRR Itay Benou, Tammy Riklin-Raviv
2018	—	`conf`	Model-dependent uncertainty estimation of medical image segmentation. ISBI Tsachi Hershkovich, Tammy Riklin-Raviv
2017	J	`jnl`	Ensemble of expert deep neural networks for spatio-temporal denoising of contrast-enhanced MRI sequences. Medical Image Anal. Ariel Benou, Ronel Veksler, Alon Friedman, Tammy Riklin-Raviv
2016	J	`jnl`	A Generative Probabilistic Model and Discriminative Extensions for Brain Lesion Segmentation - With Application to Tumor and Stroke. IEEE Trans. Medical Imaging Bjoern H. Menze, Koen Van Leemput, Danial Lashkari, Tammy Riklin-Raviv, Ezequiel Geremia, Esther Alberts, Philipp Gruber, Susanne Wegener, Marc-André Weber, Gábor Székely, Nicholas Ayache, Polina Golland
2010	—	`conf`	Resolving clustered worms via probabilistic shape models. ISBI Carolina Wählby, Tammy Riklin-Raviv, Vebjorn Ljosa, Annie L. Conery, Polina Golland, Frederick M. Ausubel, Anne E. Carpenter
2010	J	`jnl`	Segmentation of image ensembles via latent atlases. Medical Image Anal. Tammy Riklin-Raviv, Koen Van Leemput, Bjoern H. Menze, William M. Wells III, Polina Golland
2009	J	`jnl`	On Symmetry, Perspectivity, and Level-Set-Based Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. Tammy Riklin-Raviv, Nir A. Sochen, Nahum Kiryati
2008	B	`conf`	Real-time abnormal motion detection in surveillance video. ICPR Nahum Kiryati, Tammy Riklin-Raviv, Yan Ivanchenko, Shay Rochel
2008	J	`jnl`	Shape-Based Mutual Segmentation. Int. J. Comput. Vis. Tammy Riklin-Raviv, Nir A. Sochen, Nahum Kiryati
2007	J	`jnl`	Prior-based Segmentation and Shape Registration in the Presence of Perspective Distortion. Int. J. Comput. Vis. Tammy Riklin-Raviv, Nahum Kiryati, Nir A. Sochen
2007	—	`conf`	Propagating Distributions for Segmentation of Brain Atlas. ISBI Tammy Riklin-Raviv, Nir A. Sochen, Nahum Kiryati, Nir Ben-Zadok, Smadar Gefen, Louise Bertrand, Jonathan Nissanov
2006	—	`conf`	Mutual Segmentation with Level Sets. CVPR Workshops Tammy Riklin-Raviv, Nir A. Sochen, Nahum Kiryati
2006	—	`conf`	Segmentation by Level Sets and Symmetry. CVPR (1) Tammy Riklin-Raviv, Nahum Kiryati, Nir A. Sochen
2005	A*	`conf`	Prior-Based Segmentation by Projective Registration and Level Sets. ICCV Tammy Riklin-Raviv, Nahum Kiryati, Nir A. Sochen
2004	—	`conf`	Unlevel-Sets: Geometry and Prior-Based Segmentation. ECCV (4) Tammy Riklin-Raviv, Nahum Kiryati, Nir A. Sochen
2001	J	`jnl`	The Quotient Image: Class-Based Re-Rendering and Recognition with Varying Illuminations. IEEE Trans. Pattern Anal. Mach. Intell. Amnon Shashua, Tammy Riklin-Raviv
1999	A*	`conf`	The Quotient Image: Class Based Recognition and Synthesis under Varying Illumination Conditions. CVPR Tammy Riklin-Raviv, Amnon Shashua

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.