5 citations · 16 across the 7 of their papers we have counts for
7 papers
STEAM & MoSAFE: SOTIF Error-and-Failure Model & Analysis for AI-Enabled Driving Automation
Krzysztof Czarnecki, Hiroshi Kuwajima
Driving Automation Systems (DAS) are subject to complex road environments and vehicle behaviors and increasingly rely on sophisticated sensors and Artificial Intelligence (AI). The…
The missing link: Developing a safety case for perception components in automated driving
Rick Salay, Krzysztof Czarnecki, Hiroshi Kuwajima +6
Safety assurance is a central concern for the development and societal acceptance of automated driving (AD) systems. Perception is a key aspect of AD that relies heavily on Machine…
Adapting SQuaRE for Quality Assessment of Artificial Intelligence Systems
Hiroshi Kuwajima, Fuyuki Ishikawa
More and more software practitioners are tackling towards industrial applications of artificial intelligence (AI) systems, especially those based on machine learning (ML). However,…
Engineering problems in machine learning systems
Hiroshi Kuwajima, Hirotoshi Yasuoka, Toshihiro Nakae
Fatal accidents are a major issue hindering the wide acceptance of safety-critical systems that employ machine learning and deep learning models, such as automated driving vehicles…
Improving Transparency of Deep Neural Inference Process
Hiroshi Kuwajima, Masayuki Tanaka, Masatoshi Okutomi
Deep learning techniques are rapidly advanced recently, and becoming a necessity component for widespread systems. However, the inference process of deep learning is black-box, and…
Open Problems in Engineering and Quality Assurance of Safety Critical Machine Learning Systems
Hiroshi Kuwajima, Hirotoshi Yasuoka, Toshihiro Nakae
Fatal accidents are a major issue hindering the wide acceptance of safety-critical systems using machine-learning and deep-learning models, such as automated-driving vehicles. Qual…