Towards Trusted Mobile Ad-Hoc Clouds. - Ahmed Hammam; Samah Senbel (ICCTA, 2013)

A Reputation Trust Management System for Ad-Hoc Mobile Clouds. - Ahmed Hammam; Samah Senbel (Bio-inspiring Cyber Security and Cloud Services, 2014)

Multisensor Filtration and Fusion on a Three-Layer Architecture. - Mayar Tarek; Ahmed Moataz; Mennat-allah Khaled; Ahmed Hammam; Omar M. Shehata; Elsayed I. Morgan (ICVES, 2018)

Multi-Sensor Fusion for the Localization of a Small Vehicle in Outdoor Urban Driving Scenario. - Mostafa Ayman; Youssef Salem; Ahmed Hammam; El-Sayed Imam Morgan (ICVES, 2019)

Learning A Recurrent Neural Network for State Estimation using Filtered Sensory Data. - Ahmed Hammam; Mohamed A. Abdelhady; Omar M. Shehata; Elsayed I. Morgan (IV, 2019)

Multisensor Fusion Localization using Extended H∞Filter using Pre-filtered Sensors Measurements. - Mostafa Osman; Ricardo Alonso; Ahmed Hammam; Francisco Miguel Moreno; Abdulla Al-Kaff; Ahmed Hussein 003 (IV, 2019)

Real-time Uncertainty Estimation Based On Intermediate Layer Variational Inference. - Ahmed Hammam; Seyed Eghbal Ghobadi; Frank Bonarens; Christoph Stiller (CSCS, 2021)

Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety. - Sebastian Houben; Stephanie Abrecht; Maram Akila; Andreas Bär; Felix Brockherde; Patrick Feifel; Tim Fingscheidt; Sujan Sai Gannamaneni; Seyed Eghbal Ghobadi; Ahmed Hammam; Anselm Haselhoff; Felix Hauser; et al. (CoRR, 2021)

Predictive Uncertainty Quantification of Deep Neural Networks using Dirichlet Distributions. - Ahmed Hammam; Frank Bonarens; Seyed Eghbal Ghobadi; Christoph Stiller (CSCS, 2022)

Towards Improved Intermediate Layer Variational Inference for Uncertainty Estimation. - Ahmed Hammam; Frank Bonarens; Seyed Eghbal Ghobadi; Christoph Stiller (ECCV Workshops (5), 2022)

Identifying Out-of-Domain Objects with Dirichlet Deep Neural Networks. - Ahmed Hammam; Frank Bonarens; Seyed Eghbal Ghobadi; Christoph Stiller (ICCV (Workshops), 2023)

Evaluating AI-Based Components in Autonomous Railway Systems - A Methodology. - Jan Roßbach; Oliver De Candido; Ahmed Hammam; Michael Leuschel (KI, 2024)

A self-supervised text-vision framework for automated brain abnormality detection. - David A. Wood 004; Emily Guilhem; Sina Kafiabadi; Ayisha Al Busaidi; Kishan Dissanayake; Ahmed Hammam; Nina Mansoor; Matthew Townend; Siddharth Agarwal; Yiran Wei; Asif Mazumder; Gareth J. Barker; et al. (CoRR, 2024)

A-BDD: Leveraging Data Augmentations for Safe Autonomous Driving in Adverse Weather and Lighting. - Felix Assion; Florens Greßner; Nitin Augustine; Jona Klemenc; Ahmed Hammam; Alexandre Krattinger; Holger Trittenbach; Sascha Riemer (CoRR, 2024)

Structuring a Training Strategy to Robustify Perception Models with Realistic Image Augmentations. - Ahmed Hammam; Bharathwaj Krishnaswami Sreedhar; Nura Kawa; Tim Patzelt; Oliver De Candido (CoRR, 2024)