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Zhenpeng Shi, Nikolay Matyunin, Kalman Graffi, David Starobinski, "Automatic Categorization of Products for Threat Modeling", IEEE Secure Development Conference 2022, 2022.

Abstract

We consider the problem of systematizing the creation of general product categories used by libraries of threat modeling tools. Leveraging connections between various threat databases (CPE, CVE, and CWE), we propose and evaluate a method based on clustering CPE entries with the help of a knowledge graph. This clustering method allows one to categorize products, and identify the characteristics of each category based on the associated weaknesses. ...



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Chao Wang and Anna Belardinelli, "Investigating explainable human-robot interaction with augmented reality", International Workshop on Virtual, Augmented, and Mixed-Reality for Human-Robot Interactions (VAM@HRI2022), 2022.

Abstract

In learning by demonstration with social robots, a fluid and coordinated interaction between human teacher and robotic learner is particularly critical and yet often difficult to assess. This is even more the case, if robots are to learn from non-expert users. In such cases, it is sometimes troublesome for the teacher to get a grasp of what the robot knows or to assess if a correct representation of the task has been formed even before the robot ...



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Anna Belardinelli, "Estimating manipulation intentions to ease teleoperation", AIhub website (https://aihub.org/), 2022.

Abstract

No abstract...



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Muhammad Haris, Mathias Franzius, Ute Bauer-Wersing, " Learning Visual Landmarks for Localization with Minimal Supervision", International Conference on IMAGE ANALYSIS AND PROCESSING, 2022.

Abstract

Camera localization is one of the fundamental requirements for vision-based mobile robots, self-driving cars, and augmented reality applications. In this context, learning spatial representations relative to unique regions in a scene with Slow Feature Analysis (SFA) has demonstrated large-scale localization. However, it relies either on pre-existing object detectors or hand-labeled data to train a CNN for recognizing unique regions in a scene. We...



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Michael Gienger, "Bi-Manual robot manipulation - concepts and experiences", Hybrid / USA: ICRA 2022 workshop talk: Bi-manual Manipulation: Addressing Real-world Challenges , 2022.

Abstract

Invited talk at ICRA 2022 conference workshop...



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Timo Friedrich, "Three-Dimensional Voxel-Based Neural Style Transfer and Quantification", Bielefeld University, 2022.

Abstract

Machine Learning and especially Deep Learning has started to conquer another human trait in recent years by being able to perform creative tasks. Neural Network based systems compose music, create dream-like creatures, generate faces of fictional persons, and even write complete books. Accordingly, of course, they also generate visual art. Here, Neural Style Transfer stylizes images and photographs with a style extracted from an arbitrary image, ...



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Radu Stoican, Angelo Cangelosi, Christian Goerick, Thomas Weisswange, "Trust and Wellbeing in Transparent Human-Robot Interaction Teams", Centre for Robotics and AI Inaugural Conference, 2022.

Abstract

Most research in human-robot interaction focuses on either the single-human case or the multi-human case where there is direct interaction between the robot and each human. The multi-human scenario in which some of the humans depend on the robot, but do not interact with it directly, is currently less studied. In this paper, we introduce a human-human-robot collaboration task, in which the robot interacts directly with only one of the humans. The...



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Pascal Lieser, "Determination of relevant Coorperation Partners by Machine Learning", TU Darmstadt, 2022.

Abstract

In this paper, the relevance of road users for a possible future interaction is investigated. For this purpose, the concept of interaction is first discussed. This is described from various scientific perspectives using different methods and terms. Subsequently, an overall definition for interaction in road traffic is explained. In this work, a data-driven approach is followed. Several datasets containing interactive traffic situations are availa...



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Tim Puphal, Jens Schmüdderich, Nils Einecke, "Risk Estimation for Advanced Driver Assistance Systems", Biped Launch Event, 2022.

Abstract

We are invited by biped to hold a short talk at their launch event in Lausanne on 15.12. In the talk we are going to present the risk estimation developed at HRI-EU as well as a short introduction to the HRI. ...



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Christoph Bergmeir, Frits de Nijs, Abishek Sriramulu, Mahdi Abolghasemi, Richard Bean, John Betts, Quang Bui, Nam Dinh, Nils Einecke, Rasul Esmaeilbeigi, Scott Ferraro, Priya Galketiya, Evgenii Genov, Robert Glasgow, Rakshitha Godahewa, Yanfei Kang, Steffen Limmer, Luis Magdalena, Pablo Montero-Manso, Daniel Peralta-Camara, Yogesh Kumar, Alejandro Rosales-Perez, Julian Ruddick, Akylas Stratigakos, Peter Stuckey, Guido Tack, Isaac Triguero, Rui Yuan, "Comparison and Evaluation of Methods for a Predict+Optimize Problem in Renewable Energy", arxiv, 2022.

Abstract

Algorithms that involve both forecasting and optimization are at the core of solutions to many difficult real-world problems, such as in supply chain (inventory optimization), traffic, and in the transition towards carbon-free energy generation in battery/load/production scheduling in sustainable energy systems. Typically, in these scenarios we want to solve an optimization problem that depends on unknown future values, which therefore need to be...



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