13 citations · 23 across the 6 of their papers we have counts for
6 papers
Automated Configuration Synthesis for Machine Learning Models: A git-Based Requirement and Architecture Management System
Abdullatif AlShriaf, Hans-Martin Heyn, Eric Knauss
This work introduces a tool for generating runtime configurations automatically from textual requirements stored as artifacts in git repositories (a.k.a. T-Reqs) alongside the soft…
VEDLIoT -- Next generation accelerated AIoT systems and applications
Kevin Mika, René Griessl, Nils Kucza +29
The VEDLIoT project aims to develop energy-efficient Deep Learning methodologies for distributed Artificial Intelligence of Things (AIoT) applications. During our project, we propo…
Automotive Perception Software Development: An Empirical Investigation into Data, Annotation, and Ecosystem Challenges
Hans-Martin Heyn, Khan Mohammad Habibullah, Eric Knauss +4
Software that contains machine learning algorithms is an integral part of automotive perception, for example, in driving automation systems. The development of such software, speci…
Requirements Engineering for Automotive Perception Systems: an Interview Study
Khan Mohammad Habibullah, Hans-Martin Heyn, Gregory Gay +6
Background: Driving automation systems (DAS), including autonomous driving and advanced driver assistance, are an important safety-critical domain. DAS often incorporate perception…
An investigation of challenges encountered when specifying training data and runtime monitors for safety critical ML applications
Hans-Martin Heyn, Eric Knauss, Iswarya Malleswaran +1
Context and motivation: The development and operation of critical software that contains machine learning (ML) models requires diligence and established processes. Especially the t…
VEDLIoT: Very Efficient Deep Learning in IoT
Martin Kaiser, Rene Griessl, Nils Kucza +33
The VEDLIoT project targets the development of energy-efficient Deep Learning for distributed AIoT applications. A holistic approach is used to optimize algorithms while also deali…