L. Andrea Dunbar

27 papers A* 1C 1Misc 1Journal 16Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Hierarchical Training of Deep Neural Networks Using Early Exiting. IEEE Trans. Neural Networks Learn. Syst. Yamin Sepehri, Pedram Pad, Ahmet Caner Yüzügüler, Pascal Frossard, L. Andrea Dunbar
2025	J	`jnl`	PriPHiT: Privacy-Preserving Hierarchical Training of Deep Neural Networks. IEEE Trans. Multim. Yamin Sepehri, Pedram Pad, Pascal Frossard, L. Andrea Dunbar
2025	J	`jnl`	SAND: One-Shot Feature Selection with Additive Noise Distortion. CoRR Pedram Pad, Hadi Hammoud, Mohamad Dia, Nadim Maamari, L. Andrea Dunbar
2025	C	`conf`	Steerable Zero-Shot Neural Architecture Search for Efficient Edge Inference. ISCAS Simon Narduzzi, Rémy Vuagniaux, Kishan Sharma, Shih-Chii Liu, L. Andrea Dunbar
2024	—	`conf`	Constrained Zero-Shot Neural Architecture Search on Small Classification Dataset. SDS Rémy Vuagniaux, Simon Narduzzi, Nadim Maamari, L. Andrea Dunbar
2024	J	`jnl`	Learning Generative Models Using Denoising Density Estimators. IEEE Trans. Neural Networks Learn. Syst. Siavash Arjomand Bigdeli, Geng Lin, L. Andrea Dunbar, Tiziano Portenier, Matthias Zwicker
2024	J	`jnl`	PriPHiT: Privacy-Preserving Hierarchical Training of Deep Neural Networks. CoRR Yamin Sepehri, Pedram Pad, Pascal Frossard, L. Andrea Dunbar
2023	J	`jnl`	Hierarchical Training of Deep Neural Networks Using Early Exiting. CoRR Yamin Sepehri, Pedram Pad, Ahmet Caner Yüzügüler, Pascal Frossard, L. Andrea Dunbar
2023	—	`conf`	Optimizing IoT-Based Asset and Utilization Tracking: Efficient Activity Classification with MINIROCKET on Resource-Constrained Devices. WF-IoT Marco Giordano, Silvano Cortesi, Michele Crabolu, Lavinia Pedrollo, Giovanni Bellusci, Tommaso Bendinelli, Engin Türetken, L. Andrea Dunbar, Michele Magno
2023	J	`jnl`	Privacy-Preserving Image Acquisition for Neural Vision Systems. IEEE Trans. Multim. Yamin Sepehri, Pedram Pad, Clément Kündig, Pascal Frossard, L. Andrea Dunbar
2022	—	`conf`	Adaptation of MobileNetV2 for Face Detection on Ultra-Low Power Platform. SDS Simon Narduzzi, Engin Türetken, Jean-Philippe Thiran, L. Andrea Dunbar
2022	J	`jnl`	Adaptation of MobileNetV2 for Face Detection on Ultra-Low Power Platform. CoRR Simon Narduzzi, Engin Türetken, Jean-Philippe Thiran, L. Andrea Dunbar
2022	Misc	`conf`	Optimizing The Consumption Of Spiking Neural Networks With Activity Regularization. ICASSP Simon Narduzzi, Siavash Arjomand Bigdeli, Shih-Chii Liu, L. Andrea Dunbar
2022	J	`jnl`	Optimizing the Consumption of Spiking Neural Networks with Activity Regularization. CoRR Simon Narduzzi, Siavash Arjomand Bigdeli, Shih-Chii Liu, L. Andrea Dunbar
2021	J	`jnl`	Defect segmentation for multi-illumination quality control systems. Mach. Vis. Appl. David Honzátko, Engin Türetken, Siavash Arjomand Bigdeli, L. Andrea Dunbar, Pascal Fua
2021	—	`conf`	Leveraging Spatial and Photometric Context for Calibrated Non-Lambertian Photometric Stereo. 3DV David Honzátko, Engin Türetken, Pascal Fua, L. Andrea Dunbar
2021	J	`jnl`	Leveraging Spatial and Photometric Context for Calibrated Non-Lambertian Photometric Stereo. CoRR David Honzátko, Engin Türetken, Pascal Fua, L. Andrea Dunbar
2021	J	`jnl`	Privacy-Preserving Image Acquisition Using Trainable Optical Kernel. CoRR Yamin Sepehri, Pedram Pad, Pascal Frossard, L. Andrea Dunbar
2021	J	`jnl`	Wavelet Variance Maximization: A contactless respiration rate estimation method based on remote photoplethysmography. Biomed. Signal Process. Control. Duncan Luguern, Richard Macwan, Yannick Benezeth, Virginie Moser, L. Andrea Dunbar, Fabian Braun, Alia Lemkaddem, Julien Dubois
2020	—	`conf`	An Assessment of Algorithms to Estimate Respiratory Rate from the Remote Photoplethysmogram. CVPR Workshops Duncan Luguern, Simon Perche, Yannick Benezeth, Virginie Moser, L. Andrea Dunbar, Fabian Braun, Alia Lemkaddem, Keisuke Nakamura, Randy Gomez, Julien Dubois
2020	—	`conf`	Efficient Blind-Spot Neural Network Architecture for Image Denoising. SDS David Honzátko, Siavash Arjomand Bigdeli, Engin Türetken, L. Andrea Dunbar
2020	J	`jnl`	Efficient Blind-Spot Neural Network Architecture for Image Denoising. CoRR David Honzátko, Siavash Arjomand Bigdeli, Engin Türetken, L. Andrea Dunbar
2020	A*	`conf`	Efficient Neural Vision Systems Based on Convolutional Image Acquisition. CVPR Pedram Pad, Simon Narduzzi, Clément Kündig, Engin Türetken, Siavash Arjomand Bigdeli, L. Andrea Dunbar
2020	—	`conf`	Image Restoration using Plug-and-Play CNN MAP Denoisers. VISIGRAPP (4: VISAPP) Siavash Arjomand Bigdeli, David Honzátko, Sabine Süsstrunk, L. Andrea Dunbar
2020	J	`jnl`	Learning Generative Models using Denoising Density Estimators. CoRR Siavash Arjomand Bigdeli, Geng Lin, Tiziano Portenier, L. Andrea Dunbar, Matthias Zwicker
2020	—	`conf`	Remote photoplethysmography combining color channels with SNR maximization for respiratory rate assessment. ISMICT Duncan Luguern, Yannick Benezeth, Virginie Moser, L. Andrea Dunbar, Fabian Braun, Alia Lemkaddem, Keisuke Nakamura, Randy Gomez, Julien Dubois
2019	J	`jnl`	Image Restoration using Plug-and-Play CNN MAP Denoisers. CoRR Siavash Arjomand Bigdeli, David Honzátko, Sabine Süsstrunk, L. Andrea Dunbar

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.